https://orcid.org/0000-0002-0419-5816
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Abstract
We conducted a systematic review to examine whether changes in social determinants can contribute to the prevention of depression, in order to provide input for policy development and to highlight research gaps. Social determinants were defined as the structural conditions in which people live that shape their health and were categorized according to whether they pertained to societal arrangements, material resources distributed through these arrangements, or social resources that follow from interactions between people. To capture all relevant evidence we included studies that measured depressive disorders, depressive symptoms, psychological distress, mental health and prescription rates of antidepressants. We searched three databases (Medline, Embase and Psychinfo) from their inception till December 2022 and supplemented our search by reference and citation searching of the included studies. Studies were synthesized qualitatively and we used the Validity Assessment tool for econometric studies to assess study quality. Prospero submission number CRD42021236132 A total of 31,103 titles were identified, 135 studies met our inclusion criteria. The majority of studies were conducted in the United States (n = 45) or the United Kingdom (n = 39). Studies used longitudinal data (n = 61); repeated cross-sectional data (n = 20); or evaluated an intervention study (n = 7). Study designs included natural experiments (n = 19), while some used propensity score matching to construct a quasi-experiment (n = 11). Analysis methods included difference-in-difference approaches (n = 30) or regression analysis in varying forms. We found evidence that strategies that promote paid employment and parental leave policies can reduce risk of depression whereas reduced entitlements to social welfare (particularly when accompanied by obligations to enter employment), loss of income, instability of housing and collective insecurity increase depression risk. A number of studies examined moderation by gender, age category or ethnicity and of these gender was the most commonly observed moderator. Few studies tested underlying causal mechanisms with formal mediation analyses. These studies provide important indications of how intervening on social determinants of health can shape risk for depression. However, the included studies do not fully capture the complexity of the relationships between determinants and the mechanisms driving them. Future studies could take this into account, for instance by using systems approaches.
Citation: Nicolaou M, Shields-Zeeman LS, van der Wal JM, Stronks K (2025) Preventing depression in high-income countries—A systematic review of studies evaluating change in social determinants. PLoS One 20(5): e0323378. https://doi.org/10.1371/journal.pone.0323378
Editor: katsuya oi, Northern Arizona University, UNITED STATES OF AMERICA
Received: August 1, 2023; Accepted: March 27, 2025; Published: May 21, 2025
Copyright: © 2025 Nicolaou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the article and its supporting information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Globally, depression is one of the leading causes of burden of disease worldwide (ranked 13th among all illnesses) with 279.6 million people living with depression in 2019. [1]. In high-income countries, prevention interventions have mainly focused on the screening, identification and treatment of those at high-risk of developing depression across the life course, particularly in children and young people, young mothers, people of working age and older people [2,3]. Prior research indicates that selective and indicated prevention interventions are important in reducing depressive symptoms in young adults [4] and in preventing the incidence of a (new) depressive episode in the population in general [5]. Although such interventions can have an impact, a recent meta-analysis showed that incidence was only reduced by 20%, leaving 80% unaccounted for [5]. One reason for this may be that interventions target individual-level behaviours, cognitions and strategies, while the social and economic drivers of depression are rarely targeted.
There is increased acknowledgement of the role of social determinants of health in depression [6,7]. Social determinants of health are defined as “non-medical factors affecting health outcomes…the conditions in which people are born, grow, work, live and age and the wider set of forces and systems shaping the conditions of daily life” [8]. These include factors such as the built environment (e.g., blue/green space) [9], institutional structures (e.g., policy, healthcare services) [6,10], and social conditions (e.g., social cohesion, neighbourhood crime) [11,12]. The importance of the impact of social determinants is evidenced by the inequalities in depression rates between population sub-groups, i.e., the prevalence of depression is often higher in groups such as ethnic minorities and groups with a low socioeconomic status or with high deprivation, in which exposure to unfavourable social conditions is higher [13–17].
The evidence-base for the role and impact of social determinants on mental health outcomes, including depression is growing [10,11,18–21]. However, in existing studies it is often not clear whether a change in exposure to social determinants will also lead to a lower risk of depression. Establishing causality is fraught with difficulty and the increased application of counterfactual methodologies to this field has helped to clarify causality [22]. While there have been reviews of the evidence for changes in mental health and depression in relation to changes in income [21] and social security eligibility [10], an overview of the impact of a broad range of social determinants is missing. This is necessary to establish which types of (policy) interventions have the potential to improve population mental health, in particular depression, as well as to inform policy makers on possible adverse mental health effects of certain policies.
The aim of this review is to examine whether change in a diverse set of social determinants can contribute to depression prevention. The results will provide insights for policy development and highlight research gaps.
Methods
We conducted a systematic review to identify social determinants for which there is evidence for an impact on the risk of depression or depressive symptoms following changes in those determinants. The review protocol was registered in the International Prospective Register of Systematic Review (Prospero), submission number CRD42021236132. Available at https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021236132
Social determinants are the structural conditions in which people live that shape their health. We considered a determinant as ‘social if it is the outcome of an interaction between individuals [23]. This can take the form of:
- societal arrangements aimed to facilitate individuals living together in society, including the physical infrastructure, e.g., public transport, green/blue space and institutions, i.e., social norms, rules, structures impacting individual behaviour, such as the social welfare system;
- material resources distributed within societal arrangements, such as social benefits or income. Material resources not distributed through a societal arrangement, such as an increase of income due to a lottery, are excluded from this review.
- social resources that follow from the direct interaction of people in a certain context, e.g., social disorder, social participation and social capital.
Outcome measure
Our main outcome of interest was depressive disorders and depressive symptoms and we included studies that measured these outcomes using either a clinical interview or a validated screening tool such as the Center for Epidemiologic Studies Depression Scale (CES-D). In order to capture all relevant evidence, we also included studies that measured psychological distress or general mental health status such as the General Health Questionnaire (GHQ), the 12-Item and 36-Item Short Form Health Survey (SF-12/SF-36), the Mental Health Inventory 5 (MHI-5 scale), or the Kessler Psychological Distress Scale (K-6/K-10), as these questionnaires often have an item related to depressive symptoms or indicate poor mental health. Additionally, we included studies that evaluated prescription rates of antidepressant medication or other health care use indicators as a proxy outcome for the presence of depression. In the results section we describe outcomes measures as:
- Mental health or psychological distress measured by instruments such as K-6, K-10, MHI-5, GHQ, SF-12.
- Depressive symptoms based on self-reported questionnaires such as Patient Health Questionnaire (PHQ), CES-D, Beck Depression Inventory, Hopkins Symptom Inventory.
- Depression based on diagnostic interviews.
- Mental healthcare use, including prescriptions, visits to mental health care services.
Types of studies included
- Original studies that have evaluated changes in outcome measures and change in social determinants over time (two or more moments): repeated cross-sectional, longitudinal and (quasi)experimental studies including randomized controlled trials (RCTs).
- Studies set in high-income countries as defined by the World Bank [24].
- Studies that included adolescents (12–18 years) and adults aged 18 years and older.
- Studies with a sample of participants living in non-institutionalized settings.
Types of studies excluded
Studies were excluded if:
- The outcome was measured at only one moment in time, such as cross-sectional studies.
- The exposure was unrelated to a social determinant, e.g., screening for depression; stress management interventions; healthcare referral schemes.
- The study population was focused on children younger than 12 years.
- Studies in specific clinical populations or patient groups, e.g., studies among persons with diabetes, heart disease etc.
- Simulation or computational modelling studies.
- Non-human/laboratory-based studies.
- Studies set in low and middle-income countries.
Search strategy
We searched for peer-reviewed papers published in English up to December 2022. Our search terms were informed by a previous scoping review [6]; from a previous review on a similar topic [10]; and refined based on pilot searches. Three bibliographic databases were examined; Medline (including MeSH terms), Embase, and PsycINFO. The database searches were supplemented by reference and citation searching of the included studies and previously published reviews on similar topics. Search terms included three major concepts comprising a range of social determinants such as natural, structural and social environments, social and economic policy domains such as social welfare, housing, employment; outcomes (mental health and well-being, depression), and methods (quantitative). The full search strategy is included in the appendix “S1 Data”.
Title and abstract screening
Papers identified by the search strategy were uploaded in Rayyan [25] for screening. MN, LSZ and KS screened titles and abstracts of identified studies for relevance, according to the review inclusion criteria. In cases of doubt the rationale for inclusion/exclusion were discussed to reach consensus. Due to the large number of papers identified, JvdW and MN additionally screened a random set of 10% of the included papers as a check.
Full-text reviews and data extraction
The retrieved full texts were reviewed by MN and KS for inclusion. An extraction table was developed to contain general information and study characteristics (author, year of publication, country, study design, sample size), population characteristics (gender, age, ethnicity), outcome measure as described by the authors (e.g., mental health; psychological distress; depressive symptoms; depression; etc), type of social determinant studied (income, social cohesion etc.). Reasons for excluded papers were documented and are available in appendix “S2 Data”.
Studies were summarised narratively due to the wide variety of exposures and outcomes evaluated. As stated in our registered protocol, we originally planned to use the Dahlgren and Whitehead model of social determinants of health [26] as a framework to classify identified determinants at the individual, community, or societal level; however in practice it was difficult to apply this framework. For example, the introduction of a minimum wage can be categorised as a societal-level intervention but has an impact on individual-level income in those to whom it applies [27]. We therefore grouped studies based on the aforementioned categorisation building on Hahn [23]: societal arrangements; material resources; and social resources.
Outcomes were considered as statistically significant if they were below the conventional p-value cut-off of 0.05. We reported results of sub-group analyses and potential mediators when included by the original studies to understand potential differential effects by population characteristics or underlying mechanisms driving the main effect being studied.
Quality assessment
Evaluation of study quality was piloted using the Quality Assessment Tool For Quantitative Studies [28] as well as the ROBINS-I tool by Sterne JAC et al [29] as per our published protocol. However, both tools were inappropriate due to their focus on traditional study methods. We used the Validity Assessment tool for econometric studies by Barr et al. [30], a tool developed for econometric studies, which better suited the studies included in this review. The Validity Assessment includes nine component rating sections (unit of analysis; comparison approach; sample selection; number of time points of data; response bias; exogeneity of policy exposure, confounding, sample size/power and statistical methods). Overall scores ranged from 0 to 27. Consistent with Simpson et al [10], we considered studies scoring 18 or higher as high quality. MN and JvdW evaluated study quality and consulted LSZ in cases where consensus was not reached. Our quality assessment tool did not include scores for the operationalisation of the outcome measures of this review.
Results
Our search identified 31,103 non-duplicate titles: 30,961 from database searches and 142 from reference and citation searches. Of these, 116 studies (134 reports) met our inclusion criteria and were included in the final review (41 from databases and 93 via citation searching). See Fig 1, PRISMA flow diagram.
Study characteristics
A full overview of all included studies and their respective characteristics can be found in Tables 1–3. 45 studies were carried out in the USA; 39 in the UK (including England, Scotland and Wales); six in the Netherlands and Australia; five in Canada, Sweden and Spain; three in Japan, South Korea, Greece and Norway; two studies that included multiple European countries, Ireland and France; and one in Denmark, Hong Kong, Finland, New Zealand, Belgium and Germany. Most studies included adults aged 18 years and older but studies that focused on the working population included a slightly younger population aged 15/16 years and older. Eight studies included older adults, three studies (four reports) focused only on adolescents.
Most studies used longitudinal (cohort) data (n = 91); 33 studies used repeated cross-sectional data; seven studies evaluated an intervention study, five of which were randomised and two non-randomised; two studies used repeated cross-sectional data to construct a cohort. Study designs included natural experiments (n = 19), while some used propensity score matching to construct a quasi-experiment (n = 11). Analysis methods included difference-in-difference approaches (n = 30) or regression analysis in varying forms.
Based on our quality assessments, almost all studies scored equal or higher to 18 points (of maximum 27) and were rated ‘good’ quality (n = 121). Strengths included use of random population samples, inclusion of multiple covariates in models, large sample sizes and appropriate analyses; specifically, recent studies (n = 33) were more likely to employ a difference-in-difference analysis strategy. The most common weaknesses were the limited number of data-points included in the analysis, with most studies including two time points; high risk of bias through low response rates; 31 studies scored low (1 out of possible 3 points) on the ‘exogeneity of policy measure’ component of the instrument used.
The majority of studies (n = 126) used questionnaires to operationalise outcomes. Mental health and psychological distress were measured using the SF-12/36/MHI-5 (n = 16), GHQ (n = 23), the K-6/K10 (n = 12). Depressive symptoms were measured mostly using the CES-D (n = 26). Other instruments used include the Beck Depression Inventory and the Hopkins Symptom Checklist. Eight studies used short (<12 items) non-validated questions/questionnaires, e.g., mental health questions as part of a broader population heath survey. Only eight studies (nine reports) used a diagnostic clinical interview for depression. Finally, four studies analysed records of antidepressant prescriptions and seven studies used treatment claims or hospital admission data.
Results are classified in Tables 1–3 according to a single social determinant, although some studies analysed several determinants, which is reflected by those studies being mentioned more than once in Table 4.
Study findings: Societal arrangements
Included studies were sub-divided into welfare reform policies, minimum wage policies, educational policies, public transportation policies and environmental interventions, and are shown in Table 1.
Welfare reform: Tax credit policies.
Several US studies examined the effect of the expansion of the Earned Income Tax Credit (EITC) on depression symptoms or psychological distress. The EITC, implemented in 1975, was designed as a refundable tax credit to offset the rise in payroll, increasing household income. A study by Boyd-Swan et al. [31] among mothers suggests that expanding eligibility in the EITC in 1990 reduced depressive symptoms but only in married mothers. Shields-Zeeman et al. [32] leveraged variation in the size of the EITC to study the impact of changes in income and found a 2–3% of a standard deviation decrease in psychological distress per US$1000 increase in income. Two other studies found no effects of EITC payments and other income policies (including the Temporary Assistance to Needy Families (TANF) and Minimum wage policies) on psychological distress or depression risk in the short term [33,34].
Minimum wage policies.
A UK study by Reeves et al [35] evaluated the effect of introduction of the National Minimum Wage legislation in 1999 and found lower probability of psychological distress among recipients compared to similar persons who were not covered under the conditions of the new legislation. Another UK study by Kronenberg et al [36] of the same policy and using the same data source however did not observe an association. The difference in findings between the two studies maybe due to difference in construction of treatment and control groups as well as in the way wages were measured. A third UK study, by Maxwell et al [37] studied increase in minimum wage phased in over three years (2016, 2017 and 2018) and found no association with mental health. In a US study, Buszkiewicz et al [38] used state-level variation in minimum wage legislation to evaluate the association with psychological distress but found no association in the population as a whole, or on the basis of gender, age, race/ethnicity (non-white/Hispanic or white), employment status.
Expanding access to health insurance.
In 2008, the US state of Oregon opened a waiting list for a limited number of spots in its Medicaid program for low-income adults. This took the form of a lottery among the people who signed up. Finkelstein et al. [39] showed that in the first year after the lottery, winners had 10% higher probability of screening negative for depressive symptoms relative to the control group. More recently, in the context of the covid-19 pandemic, a US study by Mukhopadhyay compared data from states that expanded Medicaid entitlements with states that did not introduce such legislation. They included persons who had lost employment during the pandemic and found that those living in Medicaid expansion states were less likely to have moderate to severe mental distress following their job loss compared to those living in non-expansion states [40]. Another US study examined the effect of the Affordable care act (2014) on eligible women. Using repeated cross-sectional data the study found a lower proportion of women reporting post-partum depression after the introduction of this legislation [41].
Work incentives and employment.
Gregg et al. [42] showed that a series of welfare reforms introduced in 1999 in the UK (including in-work tax credits and welfare-to-work programmes) was associated with a decrease in psychological distress among single mothers but not in the two control groups (married and single women). Explanatory analysis indicated that the difference in trends was accounted for by markers of longer-term financial deprivation rather than employment. Harkness examined the same UK welfare reforms but restricted the categorisation of single mothers to those that had been single for more than a year in order to account for ‘transition effects’ on mental health in newly single mothers. Results indicate that being in work was associated with a significant, 12.1% reduction in psychological distress among single mothers while the effects for married mothers were not statistically significant. Overall, working lone mothers had no greater risk of psychological distress than partnered mothers [43]. In another UK study, Barr et al [44] found that reforms that re-evaluated eligibility of out-of-work disability welfare benefits (implemented in 2010) were associated with higher anti-depressant prescriptions and higher self-reported depression at the regional level. Analysing the impact of the same reform but using individual-level data Curnock et al [45], showed that transitioning from receiving disability benefits into either paid work or to ‘unemployment status’ was associated with improvement in overall mental health: scores on the SF-12 increased by 5.9 points and 3.1 points respectively.
Katikireddi et al [46] examined the impact of the ‘Lone Parent Obligation’ (LPO) reform which entailed reducing income support and mandated seeking work for welfare once women’s youngest child reached a threshold age. They found lower mental health scores in parents obliged to seek work compared with the group not exposed to reform (i.e., whose children were younger than the threshold age).
Wickham et al. [47] investigated the impact of Universal Credit reform, which was intended to provide greater incentives for claimants to enter employment. The results indicated higher psychological distress and poorer mental health in those eligible for Universal Credit after implementation of the reform. Williams [48,49] also examined the mental health impacts of restrictions on unemployment benefit (Job Seekers Allowance), in the form of benefit sanctions, implemented between 2010 and 2012. The results indicated that for every 10 additional sanctions applied per 100,000 population the rate of antidepressant prescriptions was 1.74 items higher (2019 study). Analyses in a larger number of districts showed higher rates of self-reported anxiety and depression (2021 study). For both outcome measures (antidepressants prescriptions, self-reported depression), a further increase was observed after the sanction policies became more severe (from end of 2012): every 10 additional sanctions applied per 100,000 population were associated with 4.57 additional antidepressants prescribing items (p < 0.001).
We included three US studies on welfare reforms that aimed to move single mothers from welfare to work. Jagannathan et al. [50] studied the New Jersey Family Development experiment, showing that women in the intervention, which stressed welfare-to-work experienced higher odds of clinical depression (based on Medicaid claims) compared to controls that continued to receive traditional welfare benefits. Rote et al [51] studied the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA) which requires mothers to work in return for assistance and limits total federal lifetime TANF eligibility to 60 months. After reform, welfare recipients reported significantly more depressive symptoms than other women living in poverty when compared to the period before reform. Morris [52] also examined health impacts of the PRWORA by focussing on whether emphasis on quick job entry and/or personal attention in making the transition to employment made a difference in depressive symptoms. Clients of programs in the highest quartile of emphasis on quick job entry, particularly those with preschool children, experienced higher depressive symptoms based on CES-D score, when compared to the control group (clients not subject to changes in welfare package). Personalised support by caseworkers had no effect on depressive symptoms.
Parental leave policies.
We found nine studies that examined the impact of parental leave policies, all published in the past eight years. Most studies leveraged changes in maternal or family leave policies as a natural experiment.
We included four studies from the US. In a longitudinal study among 72 couples expecting their first child, Cardenas et al. [53] found that mothers whose partners took paid paternity leave had smaller prenatal-to-postpartum increases in depressive symptoms, whereas no difference was observed in the fathers themselves. Three studies examined the impact of implementation of paid family leave policy in California, which was the first US state to implement such a policy, in 2004. In a difference-in-difference analysis, all three studies [54–56] showed reduced psychological distress levels after the implementation of that policy, both among mothers and fathers.
Australia adopted a national paid parental leave policy in 2011. Two studies showed improved mental health among mothers after the policy had been implemented [57,58]. In addition, Bilgrami et al. [57] showed that the impact on mental health was larger among those mothers whose partners had access to a complementary policy specifically for partners.
The three European studies showed similar results. Avendano et al. [59] used data from the SHARE study, a panel survey of a representative sample of the European population aged 50 + , finding that paid maternity leave in seven European countries was associated with lower depressive symptoms in older age. The other two studies were designed as natural experiments, and studied the impact of policy changes in Norway and Denmark [60,61]. In Norway, a national paid maternity leave arrangement was implemented in 1977 and Bütikofer et al [61] found improved maternal mental health after the introduction of this policy. On the basis of complementary research on explanatory variables, the authors suggest that improvements were mainly driven by the mother spending more time at home after childbirth [61]. A Danish study on the impact policy reform that increased in the length of maternity leave (from 24 to 46 weeks of fully compensated leave) did not show a reduction in hospitalisation due to depression or use of anti-depressant medication among mothers [60].
Pension policies.
We found two studies that examined the impact of increasing pension age. In the Netherlands, de Grip et al. [62] found that a 2006 reform that increased pension age from 62 years and three months to 63 years and four months had a sizable impact on depressive symptoms: two years after the policy change high depressive symptoms were about 40% higher in participants exposed to the reform as compared to those not exposed. This was particularly so in participants that experienced a larger income loss because of the reform. In a UK study among women Carrino et al. [63] found that a reform that gradually increased the State Pension Age from 60 to 66 years within a short time-frame (10 years) led to an increased the likelihood of psychological distress and poor mental health. This effect was confined to women in jobs with high demands and low control.
In a Korean study, Kim et al. [64] examined the introduction of a Basic Old-Age Pension (BOP) in 2008, which provided a fixed pension for older persons in the lowest income category considering household income and assets. The association between receiving the BOP and depressive symptoms was not statistically significant, however, the authors reported that although the BOP improved income, it was not substantial enough to resolve poverty or relative deprivation, which may explain the lack of effect observed.
Housing benefits.
A UK study by Reeves et al. [65] evaluated the impact of cuts in the Government Housing Benefits - a programme which provides funds for tenants who rent housing in the private sector - on depressive symptoms in low-income households. The study found that the financial cuts to the housing allowance scheme (approximately 2,300 USD per year) significantly increased the prevalence of depressive symptoms by 10%.
Childcare benefits.
A Canadian study by Lebihan and Tangkomo [66] examined the effect of the Universal Child Care Benefit which provided for an unconditional cash transfer to families with children aged up to 6 years. The study found a small but non-significant improvement on depressive symptoms with indications of a stronger beneficial effect in families with low parental educational level and in families with girls.
Public transportation policies.
Reinhard et al. [67] examined the impact of the introduction of free bus passes to adults aged 60 years and older. Results showed that public transportation use increased after introduction of the policy and the policy was associated with a reduction of depressive symptoms. Based on the results on the association between transport use and possible explanatory factors the authors suggest that the benefits may stem from reduced loneliness, increased participation in volunteering activities and increased contact with children and friends.
Educational policies.
We found only one study that examined the impact of years of education on depressive symptoms. Hamad et al. [68] took advantage of variation in United States state-level compulsory schooling laws, a natural experiment that was associated with geographic and temporal differences in the minimum number of years that children were required to attend school. They found that increased years of education was associated with lower depression rates based on CES-D-8.
Environmental noise exposure.
Two studies examined the effect of environmental noise exposure. In a US study Wang et al observed an increase in depression diagnoses (based on Medicaid claims) in two New York neighbourhoods that were subject to increased air traffic noise due to redirection of flight paths [69]. A study in the Netherlands examined changes in depressive symptoms in an older population after introduction of policy to reduce aircraft noise levels. The authors observed that the policy failed to achieve its goal and there was no change in population-level symptoms [70].
Study findings: Material resources
Following data extraction, the included studies on material resources were classified into 4 categories: income, employment, housing and collective material insecurity (Global Financial Crisis). The findings are shown in Table 2.
Income supplement.
Costello et al [71,72] evaluated the effect of increase in income due to a newly opened casino on a native-American reservation on mental health of children. Residents profited in terms of paid jobs and through receiving a fixed income in the form of percentage of the generated profits. There was no significant difference in depression or anxiety outcomes either 4 or 10 years after the opening of the casino, although children whose families moved out of poverty (14% of all children) had significantly fewer behavioural problems. Another US study by Courtin et al [73] examined the effects of a conditional cash transfer to families, contingent to spending money on education, preventive healthcare and parental employment, but found no effect on psychological distress.
Income volatility.
Income volatility refers to the year-to-year change in income for an individual or a household. The majority of studies on income volatility reported deterioration in depressive symptoms with reduced income.
Prause et al [74] found that downward income volatility was associated with higher depressive symptoms over a 6-year follow up period. However, this association was not significant when absolute volatility (regardless of the direction of change) was low. The authors propose that downward income change, rather than change per se, affects depressive symptoms. This view is consistent with findings of Sareen et al [75], Benzeval et al [76], Barbaglia et al [77] and Lorant et al [78], which found that a decrease in income was associated with depression incidence, psychological distress and depressive symptoms respectively. Two studies focused on poverty transitions. Wickham et al [79] found that transitioning into poverty, defined as < 60% of national median household income, was associated with increased psychological distress. Thomson et al [80] found that the negative effects on psychological distress when transitioning into poverty were stronger than the positive effects of transitioning out of poverty. Several studies examined changes of financial status within the context of the 2008 Global Financial Crisis (GFC): Lindstrom et al [81] found that worsened financial status after the crisis was associated with higher risk of psychological distress, whereas improved financial status was not; Swift et al [82] found that income drop was associated with higher depressive symptoms. Curl and Kearns found that increased financial difficulties, in relation to austerity measures post GFC, was associated with reduced mental health [83].
One study examined the influence of loss in wealth. Within the context of the GFC, McInerney et al found that reduced wealth was associated with increased depressive symptoms and use of antidepressants among adults aged 55 years and older, with these effects being larger among respondents with high levels of stock holdings prior to the crash [84].
No association with changes in income were reported by two studies. McCarthy et al [85], included US and Canadian participants and found no association between changes in income with either depressive symptoms or mental health, although this effect was mediated by material hardship. McKenzie et al [86], in a study of changes in socio-economic status found no evidence that reduced household income was associated with psychological distress or mental health.
Employment.
Studies on employment focused on loss/gain of employment, reduction of working hours or changes in employment quality. Overall, gaining employment was associated with lower depressive symptoms over time [87–96] while losing employment or having working hours reduced was associated with increased risk of depression [77,86,91,97–99]. Similarly, low quality employment trajectories, such as job instability and cumulative disadvantage were associated with higher risk of depression [100–103]
Studies looking at the effects of employment on depression reported some demographic differences. Lahelma [96] found that registered job-seekers who obtained a paid job had four times lower the odds of psychological distress than those who remained unemployed; this effect was stronger in men than in women. Differential effects based on gender were also observed by Jonsson et al [102], Hoven et al [101] and Kim at al [99]. Ali & Avison [104] found that transition either in- or out- of paid work was not associated with changes in depressive symptoms for the combined sample but losing work was associated with increased depressive symptoms in single compared to married mothers. Two studies by Eisenberg-Guyot et al in the US and Brudsten et al in Sweden and observed that ethnic minorities were more likely to experience adverse employment trajectories, which in turn was associated with reduced mental health [100,103]. Other studies reported that psychological resources and financial strain partly explained findings in single mothers transitioning out of work [105–107]. Zabkiewicz et al [106,107] examined the effects of gaining employment in single mothers receiving Temporary Aid to Needy Families (TANF), which carries a condition that recipients seek work. The authors found that gaining employment was associated with lower depressive symptoms, but effects were not observed in substance users or in women with more than three children. Breslin and Mustard [108] found that becoming unemployed was associated with higher risk of depression over a timespan of two years, but only in adults aged 31–55 years. Using data from an older population, Gallo et al. [109,110] investigated whether involuntary job loss due to a business closing or layoff was associated with changes in depressive symptoms and found that in the long term (4–6 years) the initial association with depressive symptoms was only present in those with low financial means (2006 study). Only two studies, Lorant et al. and Salm [78,111] reported no association between becoming unemployed and depressive symptoms.
Job security.
Two studies considered the impact of the threat of job loss. In a study of British Civil servants, Ferrie et al. [112] showed that those reporting changes in job security (but not job loss) over a 2.5 year period had higher psychological distress compared to consistently job secure participants.
A Swedish study by Magnusson Hansen et al. [113] indicated that risk of dismissal was associated with higher depressive symptoms, particularly for participants reporting consistent threat. The authors also found evidence that depressive symptoms influenced how a person perceived threats of dismissal.
Housing.
Studies considering housing included multiple components such as quality and affordability, both at the individual level as at the neighbourhood (collective) level. At the collective level, exposure to neighbourhood characteristics might change either because of improvements in the environment, or as a result of residents being relocated to a more favourable neighbourhood.
Housing Quality at the individual level: Adequacy.
A UK study by Blackman et al. [114] studied the health impact of reallocation of social housing based on medical needs. The study found larger improvements in mental health in participants that obtained housing conform their needs compared to participants still on a waiting-list, but no differences in the use of antidepressants. Petersen et al. [115] found that a selective licencing scheme, which aimed to improve rental housing quality was associated with lower area-level mental healthcare use. Pevalin et al found that persistently living in poor housing was associated with poor mental health and that having experienced this over a longer timeframe had effects over and above the current housing situation [116].
Housing at the individual level: Affordability and stability.
In the US, Denary et al. [117] studied the effect of affordable housing in low-income adults by comparing those receiving rental assistance with those either wait-listed or not receiving assistance. The study found decreased psychological distress among participants that obtained rental assistance, but this was not statistically significant.
Three U.S. studies found increased risk of depression with housing eviction [118–120]. Conversely, another US study, conducted during the covid-19 pandemic, found that states with strong moratoriums on housing eviction had lower prevalence of depressive symptoms. This effect was stronger in Hispanic and non-Hispanic white populations that in African Americans [121]. A UK study by Prevalin [122] found a positive association between housing repossession (i.e., in the case of home ownership) and psychological distress. Participants evicted from rental properties showed a slight increase before the event but this effect did not persist. Using the same study population, Taylor, Pevalin and Todd found that going into payment arrears (either rent or mortgage payments) was associated with psychological distress [123]. This was also observed in a study by Alley et al, that examined mortgage delinquency [124] and by Kim et al, when housing became unaffordable [125]. The latter study observed that depressive symptoms reduced in those who moved into affordable housing [125].
Finally, instability in housing, characterised by having multiple addresses over time was associated with higher depressive symptoms in two US studies [126,127].
Housing at the collective level: Economic (dis)advantage.
Leventhal et al. [128] studied the “Moving to Opportunity” experiment in New York (US) to assess the to assess the effect of moving from a high-poverty to a low-poverty area in families with children. Parents that moved to low-poverty neighbourhoods reported fewer depressive symptoms than those who remained in high-poverty neighbourhoods.
Cooper et al [129] assessed the effects of a housing relocation programme in residents of public housing and found that moving to an area with less economic deprivation was associated with reduction of depressive symptoms. McKenzie et al [86] reported no association between change in area-level deprivation score and psychological distress over a five-year period among a general sample of the population.
Housing at the collective level: Urban regeneration programmes.
Eleven studies examined the effect of multi-component urban regeneration programmes on the mental health of residents. Harvey [130] used a pre-post design to examine changes in mental health following housing improvements in a Scottish neighbourhood and found 15% reduction in psychological distress following regeneration. Huxley et al. [131] examined the impact of the Single Regeneration Budget area in Manchester and found that the prevalence of psychological distress did not differ between the intervention versus control neighbourhoods at follow-up. Although some improvements had been observed in the intervention areas, the authors noted that little of the available budget was spent, which might explain the lack of an effect.
Rose et al examined the Community Wealth Building programme in one of the 20% most deprived local authorities in the UK. The programme was designed to boost economic development through, for example, improved employment conditions and support of local supply chains by public and non-profit organizations. This resulted in reduced antidepressant prescriptions and prevalence of depression relative to the control areas [132].
The UK New Deal for Communities (NDC) programme (1999–2011) was studied by Stafford et al. [133] and Walthery et al [134]. The programme targeted 39 of the most deprived areas in England, with activities in multiple domains (crime, physical environment, community etc.). Stafford et al observed a decline in psychological distress in some intervention areas between 2002 and 2008, however, the difference with comparator areas was not significant. Using longitudinal data from each of the NDC areas, Walthery et al. also did not find evidence that the programme impacted mental health, although respondents in poorer socio-economic circumstances in NDC areas fared better than those in comparator areas.
White et al. [135] and Greene et al. [136] report on the impact of ‘Communities First’, an area-wide regeneration programme delivered in the 10% most deprived areas in Wales. The programme addressed multiple themes, such as crime, education, and building community facilities. After the intervention period, mental health in the intervention group was better than in comparable areas. Mediation analysis [136] indicated that over half of the observed effect was explained through improvements in neighbourhood quality (littering, nuisance from dogs and noise: 22%), reductions in disorder (vandalism, crime rates and discarded needles and syringes: 19%) and sense of neighbourhood belonging (11%) and, for a small extent, by social cohesion (1.7%).
Egan et al [137,138] assessed effects of an urban renewal programme in 14 deprived neighbourhoods in Glasgow, Scotland. The programme, addressed housing quality, as well as social factors (e.g., debt payment services, playgrounds, employment support). Using data from 2006–2008, they found small improvements in mental health among residents experiencing housing improvement compared to residents of similarly deprived non-target areas. A follow-up study from 2006 to 2011 found that improvements in mental health were higher in areas with greater financial investment compared to lower investment areas.
Two studies in the Netherlands examined the impact of an urban regeneration programme, implemented between 2008 and 2011 in deprived neighbourhoods. The programme included multiple interventions, such as creation of green space and facilities for sport, improving safety and social cohesion. Jongeneel et al. [139] found that the trend change in mental health between the intervention and pre-intervention period was approximately the same in the target districts as in deprived control districts. Improvement in mental health was found in those target districts that implemented a more intensive programme. A study by Timmermans et al. [140] in a cohort of older participants found no evidence of an effect of this programme on depressive symptoms.
Collective material insecurity: Financial crisis.
The impact of the Global Financial Crisis (GFC) of 2007/8 and subsequent austerity policies on mental health has been examined in several countries; Hong Kong, Greece, Ireland, Spain, France, the US, UK and Canada and across Europe. Only three studies found no changes in population-level depressive symptoms post GFC [141–143].
Several studies examined the specific conditions under which risk of depression was increased. In addition to the studies described in the section on ‘Income volatility’, earlier in table 2 [82–84], Lee et al. [144] found that the prevalence of depressive episode was higher in those experiencing loss in financial investments. Madianos et al. [145] and Economou et al [146] found higher depression in cases of financial hardship or in people who experienced higher economic distress. Modrek et al. [147] examined changes in utilization of mental health services and medications in a cohort of continuously employed (and insured) workers of a manufacturing firm in the US that experienced significant downsizing events during the GFC. The results showed that workers used more antidepressants after the recession (13%), which contrasted with a decreasing trend of use before the recession and that this effect was stronger in high lay-off plants.
In a study across 20 European countries, Buffel, Van de Velde and Bracke found increased prevalence of depressive symptoms in countries with increased unemployment rates post GFC, taking the economic state of each country before the crisis into account but found that these contextual effects were not fully explained by differences in individual-level employment [148]. Drydakis et al [149], Bartoll et al [150], Gili et al [151] observed an important role of individual-level unemployment in the higher risk of depression. Barr et al reported that increased area-level unemployment and decreased area-level income explained a large part (36%) of the decline in mental health observed post GFC [152]. The role of austerity measures was examined by two studies, Nour et al. [153] initially found no association between exposure to GFC and self-reported depression diagnosis by a physician but an increase herein after subsequent implementation of austerity measures in 2011–13; Cherrie et al. [154] showed that reduced area-level employment levels were associated with increased incidence of antidepressant use and that austerity measures such as reduced eligibility for welfare payments, and subsequent income reduction explained a large proportion of the observed effect. Two studies looked at ethnic differences in the effect of the GFC: An Irish study by Villarroel et al observed that depression post-recession was only increased in Irish men but not in non-Irish or African-origin men [155]; Gotsens et al observed that the development in mental health of immigrant women (but not men) was less favourable than among Spanish-born residents [156].
Finally, in an older study, of the 1991 economic recession in Sweden, Rahmqvist and Carstensen observed higher prevalence of psychological distress compared to pre-recession years. This effect was observed in both employed and unemployed persons [157].
Study findings: Social resources
Following data extraction, the included studies on social resources were classified into two categories: social disorder (n = 4), and social participation (n = 7). See Table 3.
Social disorder.
Social disorder represents elements that result from the behaviour of people living in a particular environment such as safety, crime, violence, graffiti etc [158]. A US study by Cooper et al. [129] showed that relocation to neighbourhoods with lower social disorder (operationalised by violent crime rates and density of alcohol outlets) as part of a public housing relocation programme was associated with a persistent reduction in depressive symptoms during follow-up in both men and women. The change seemed to be driven by changes in perceived crime. Another US study by Mair et al. [159] found that increased neighbourhood safety, social cohesion and aesthetic quality were associated with lower depressive symptoms while increases in neighbourhood violence and stress was associated with increased depressive symptoms although the small sample size meant wide confidence intervals for all indicators.
Using longitudinal data on exposure to neighbourhood crime rates (non-domestic violence, malicious damage to property, break/enter, stealing/theft/robbery), Astell-Burt et al. [160] reported that an increase in neighbourhood crime was associated with greater psychological distress. Effect sizes were particularly high for women, especially when an increase in malicious damage was observed in the neighbourhood. In the UK, Dustmann & Fasani [161] examined the effect of local crime rates on psychological distress, using two large British panel surveys. Their findings showed a statistically significantly negative impact of overall local crime rates on psychological distress, especially in women.
Social participation.
This category includes studies that looked at different aspects of social interaction between individuals.
An Australian study by Cruwys et al. [162] examined whether depressive symptoms can be prevented by increasing social contact and facilitating social identification. Fifty participants at risk for depression (previous diagnosis of mental illness) joined a community recreation group; joining a social group was associated with a reduction in depressive symptoms among participants who reported identifying with the group. A study in Ireland by McGale et al [163] examined the effect of promoting social support within a supervised exercise intervention, compared to supervised exercise alone or a group that had access to unsupervised exercise facilities. The study found that engaging in supervised exercise was associated with reduced depressive symptoms but there was no additional effect in the group that received the social support component.
Three of the included studies were conducted in Japan. Murayama et al. [164] examined the effect of reading books to young children at school on elderly persons’ depressive symptoms. The study found that participation was positively associated with sense of manageability and meaningfulness; which in turn was negative associated with depressive symptoms. Watanabe et al. [165] examined whether municipal-level social capital was associated with depressive symptoms. Improvement in ten out of the 14 indicators of social capital were associated with a decline of prevalence of depressive symptoms.
Finally, a UK study by Lindström & Giordano [81] examined the impact of changes in social capital in relation to psychological well-being against the background of the GFC, with social capital operationalised as level of trust and social participation. The results indicated that individuals with low levels of trust in 2008 had increased psychological distress in 2008 compared to 2007, even after considering individual perceptions of financial strain.
Table 4 provides a summary of the main findings based on the categorisations applied.
Discussion
In this review, we aimed to examine whether changes in social determinants can contribute to the prevention of depression, to provide input for policy development and to highlight research gaps. We found most, consistent and high quality of evidence for changes in a number of social determinants, where a positive development led to a reduction on risk of depression 1) paid parental leave (8/10 studies) 2) gaining employment (9/10 studies); or, conversely, where a negative development led to increased risk of depression 1) reduction in income or transitioning into poverty (12 studies), 2) losing employment (14/17 studies), 3) work incentives coupled with reduction/loss of welfare ((8/12 studies), 4) collective insecurity (economic crisis) (14/18 studies), instability of housing (9 studies). We present the main findings according to our categorisation of whether interventions addressed societal arrangements, material resources distributed through these arrangements, and social resources that follow from interactions between people. In order to streamline the discussion we make use of ‘risk of depression’ as umbrella term to cover all outcomes specified in the findings.
Societal arrangements
The majority of studies on societal arrangements assessed the impact of welfare reforms. All of the studies can be considered high quality, i.e., > 18 points on the Validity Assessment scale. Of those, five studies scored 19–20 points. Most studies examined restriction of entitlements to social welfare and found that restriction of entitlements was associated with increased risk of depression. This finding is largely consistent with another recent review [10]. However, some studies reported that reforms in work incentives and employment also resulted in a reduction in depression risk. In the latter group of studies, changes in entitlements were accompanied by a wider package of incentives such as tax credits [42] or transitioning to another category of entitlement [45]. The studies on expansions of welfare entitlements, such as tax credit policies, showed either reduction in risk of depression or no effect (in the short-term). In this category and consistent with a recent review by Heshmati et al, paid parental leave policies most convincingly showed a positive effect, in particular among mothers [166]. The impact on fathers was less studied.
We found four studies that evaluated minimum wage policies and only one study each looking at educational policies, public transport policies, and environmental policies, limiting our ability to generalise these findings.
Material resources distributed through these arrangements
The determinants for which we found consistent evidence were generally studied in a range of countries. Becoming unemployed, for example, was related to increased risk of depression and was observed by studies in the US, Norway, Netherlands, Canada, UK, Spain and New Zealand, Sweden, South Korea, Japan, France, Belgium, Germany, Finland and Australia. Study quality was mixed, of the 28 studies related to employment, 11 scored less than 20 and of these five scored less than 18 points. Thus our findings regarding employment may be biased, although they were similar to those of previous reviews and meta-analyses [167,168]. The association between employment and risk of depression was consistent over time but may have changed in recent years due to changes in the labour market. For example, an ageing workforce, technological advancements, and economic shocks such as the global pandemic as well as the rise of the gig economy [169]. Ten of the 26 studies identified in our review were conducted post-2010, potentially capturing the effect of these changes, particularly the studies examining labour market trajectories/precarity [98,100–103]. However, the design of these studies means it is not possible to identify the conditions in the labour market that impact on the association between employment and mental health. This indicates a need for additional studies on the mental health impacts of (un)employment, that clarify the conditions under which employment can contribute to reducing risk of depression.
Evidence for the effect of income loss was much stronger than for a gain in income, although study quality was generally lower than for other determinants studied with 6/12 studies scoring higher than 20 points. Our finding is consistent with the results of a meta-analysis that also included low- and middle-income countries [21]. The negative effect of income loss was found to be stronger in those with lower income levels or close to poverty, as is also discussed by Shields-Zeeman and Smit [22]. In our review only two of the seven studies found this negative effect of income to be specific in lower income groups [78,79] implying that in the case of high-income countries the underlying mechanism for this effect is not restricted to absolute poverty. It is likely that experiencing relative poverty might act, for example, through perceptions regarding societal standing (status anxiety) or stigma associated with being poor.
Studies on housing at the collective-level, through urban regeneration showed mixed results. About half of these studies indicated no positive impact on risk of depression. The other half indicated an impact, primarily within subgroups (e.g., women) or in areas with higher realised investment.
Social resources that follow from the interaction between people
This was the least studied set of social determinants. Improvement and deterioration of social disorder at the neighbourhood level was consistently associated with a lower and higher risk of depression respectively. Three of the five studies on social participation showed that increase therein was followed by a reduction in risk of depression, although study quality was low, with low numbers of participants
Determinants with limited evidence
For a number of social determinants examined by studies in this review, we had insufficient evidence to draw a conclusion on its (in)effectiveness. This specifically applied to expansions in access to social welfare other than paid parental leave policies, societal arrangements other than welfare reforms, increased income, urban regeneration programmes, and social participation. The reasons for the insufficiency of the evidence varied from a limited number of studies with limited variation in settings (e.g., expansions to social welfare through Earned Income Tax Credit programmes or access to health insurance), mixed results without having insight into the reasons for this (e.g., urban regeneration programmes) or too limited to draw a conclusion (e.g., social capital). For housing security, the results were inconsistent across spatial levels; at the individual level, studies consistently indicated a change in risk of depression, negative and positive following deterioration or improvement respectively of housing insecurity, affordability or threat of eviction. Studies at the neighbourhood level, including urban regeneration yielded mixed results which cannot be ascribed to low study quality; only one of the 11 studies scored <18 on the Quality Assessment scale. The difference in results between these two types of studies may be due to the fact that in studies at the individual level, the exposure consisted of a clearly defined improvement or deterioration, e.g., housing eviction, whereas the change in exposure at the neighbourhood level, in urban renewal programmes, was less clearly defined, often including multiple unspecified changes. Interestingly, studies aimed at the social and community environment with a more specific focus, such as crime levels [128,129,160,161], social cohesion [159,165], gave a more consistent picture, i.e., improvements in depression risk with improvement in exposure.
Strengths and limitations
The focus of this review was on depression. However, the majority of the studies included measure more general constructs like psychological distress or mental health. There is a dearth of research on the impact of changes in social determinants on rates of depression at the population level. While this information is highly relevant, obtaining such data is highly challenging. Moreover, the field is currently moving more towards broader outcomes such as wellbeing and functioning. In order to capture as many studies focused on intervening on a social determinant as possible we chose to expand our inclusion to these broader outcomes.
We aimed to develop an overview of potential policies and intervention that act on social determinants of mental health relevant for high income country contexts, and we may have missed specific mechanisms at play in low and middle-income country contexts. Excluding low and middle-income countries in our search means that we might have missed capturing the mechanisms underlying the association between these determinants and depression. However, the influence of the social determinants can be very context-specific. For example, the level of economic development is likely to influence the impact of such interventions, especially progressive policies like parental leave, although there is likely to be variation in contextual factors between high-income countries as well.
Our search strategy was very broad and we did not include a limitation on publication date to avoid missing older studies. The broad inclusion of determinants means that we were only able to conduct a qualitative synthesis of the included papers and relied on authors’ reporting for any quantitative evaluation of findings in terms of meaningful effects. We also may have missed some relevant articles, as our search terms may not have been exhaustive for some topics, such as social participation, which can be operationalised in a variety of different ways, including social cohesion or social capital [12]. We conducted our search in three major databases (Medline, Embase and Psychinfo) so some relevant papers may have been missed. To compensate, we conducted a thorough search of the reference lists of included studies and published reviews. Finally, we restricted our focus on studies that examined change in both determinant and outcome, which likely explains the limited numbers of studies included on some topics, specifically, on social resources which has been the topic of other reviews [170,171]. Nonetheless, we believe our approach helped capture the state of the art with regards to the potential for interventions to prevent depression across a broad range of social determinants.
Implications for further research
Limiting our search to studies that included change in both determinants and outcomes was useful in expanding our understanding of what can be expected from interventions addressing social determinants; as not all associations between such determinants and depression are causal. Consequently, a broad range of determinants, identified in observational studies, has not been included in this review. For example, social norms towards mental illness, social pressure, status anxiety, excessive use of social media, exposure to noise, green/blue space etc [6,12,172,173]. This emphasizes the need for studies with similar designs as included in our review on a much broader range of social determinants than currently studied.
The included studies used a variety of instruments and outcome measures, some of which specifically assessed depressive symptoms. An important area for consideration in future research is to ensure that large cohort studies, also those that include clinical assessment of depression, expand measures to include a variety of social and economic risk factors, either by adding these variables to their data collection process or linking their data to other databases on (changes in) social determinants.
As previously mentioned, studying change in the social determinants of health is fraught with difficulty, e.g., populations cannot be randomized to a particular condition to adhere to the gold standard of a randomized controlled trial (RCT). A number of the included studies used natural experiments or instrumental variables where an RCT may not have been possible or appropriate. However, the application of such methodologies remains limited and could be explored more by researchers as could the potential of applying new causal inference methods in the evaluation of interventions. Further, although many authors discussed potential mechanisms underlying the relationships observed few studies included in our review employed formal mediation analysis to try and unravel such mechanisms which indicates the need for more mechanistic studies in this field.
Although alternative experimental designs, causal inference and mediation analysis help expand our understanding of the role of individual social determinants in depression, they do not reflect complex reality, where multiple factors act at different levels of influence, ranging from the individual- to the social- and environmental-levels. This need is perhaps mostly clearly illustrated by the studies evaluating widely divergent, multi-component interventions (i.e., urban renewal interventions), studies with differential effects depending on population characteristics and in studies with no clear direction of effect, such as studies of policies to incentivise employment. To capture this complexity, there is a need to apply systems approaches [174] and realist approaches [175], focusing on questions such as: under which conditions do changes in social determinants influence depression and for whom; how do different determinants of mental health/depression (e.g., social cohesion and economic improvement in a neighbourhood or in the urban environment interact in their impact on mental health? In taking this approach it is important to include consideration of the role of political, economic, or logistical constraints in adoption of policy to address the social determinants of health.
Implications for policy
Traditional approaches to improve mental health or prevent depression often target the individual and their role in shaping their own outcomes. This focus on the individual suggests that the responsibility to overcome barriers such as poverty lies with the person rather than with allocation of resources by governments and institutions [176]. Focusing on social determinants as a way to impact depression levels proceeds from the premise that even relatively small shifts in the distribution of depressive symptoms at the population-level could be expected to have large benefits for the population as a whole [177]. This is relevant considering the relatively high societal and healthcare cost of even mild depressive symptoms [5,178].
We found consistent evidence for policies aimed at providing paid parental leave; promoting paid employment; and preventing income loss/financial distress. Importantly, our review has shown the importance of mitigating financial insecurity (through austerity measures) in a context of financial crisis, as well as preventing job insecurity.
Our review also highlights the importance of considering the unintended consequences of policies. For instance, reforms that incentivise employment may impact other factors the influence mental health. The Job Seekers Allowance in the UK [47–49] and the introduction of the Personal Responsibility and Work Opportunity Reconciliation Act in the US [51,52]), were both consistently followed by an increase in depression risk, probably through their restriction of welfare benefits. Other negative effects of incentivising work maybe due to increased need for childcare or insecurity due to having to take on menial, unstable work.
The lack of clear-cut evidence on many of the other determinants included in this review was due to limited numbers of studies or methodological issues, thus we cannot conclude that they are not relevant for policy.
Overall, the broad spectrum of actions needed to address population-level depression risk implies there is a need for a comprehensive approach that involves collaboration between different policy domains. In addition, the complexity of addressing population mental health, given interactions between different determinants, differential effects across populations and unintended consequences implies careful consideration of the local context in developing policy, preferably using system dynamic approaches.
Conclusion
This review builds upon reviews of observational and longitudinal studies that show an association between social determinants and risk of depression. We wanted to extend that evidence by studying whether this association can be influenced/changed through policy or intervention and to identify gaps in evidence. Overall, we found evidence that population-level depression risk can be reduced by policies ensuring the provision of paid parental leave; prevention of income loss/financial distress; and the promotion paid employment. Whereas reduced or conditional entitlements to social welfare, loss of income and financial distress, loss of employment and collective insecurity can increase depression risk. We argue that there is a need for studies on a broader set of social determinants using systems and realist approaches to understand the complex interactions between determinants and contextual factors.
Supporting information
S2 Data. Overview of included and excluded papers.
https://doi.org/10.1371/journal.pone.0323378.s002
(XLSX)
References
- 1. GBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9(2):137–50. pmid:35026139
- 2.
WHO preventing depression in the WHO European Region.pdf.
- 3.
Smit F.S. Petrea I. Preventing depression in the WHO European region. 2016
- 4. Breedvelt JJF, Kandola A, Kousoulis AA, Brouwer ME, Karyotaki E, Bockting CLH, et al. What are the effects of preventative interventions on major depressive disorder (MDD) in young adults? A systematic review and meta-analysis of randomized controlled trials. J Affect Disord. 2018;239:18–29. pmid:29990660
- 5. Cuijpers P, Pineda BS, Quero S, Karyotaki E, Struijs SY, Figueroa CA, et al. Psychological interventions to prevent the onset of depressive disorders: A meta-analysis of randomized controlled trials. Clin Psychol Rev. 2021;83:101955. pmid:33333441
- 6. van der Wal JM, van Borkulo CD, Deserno MK, Breedvelt JJF, Lees M, Lokman JC, et al. Advancing urban mental health research: from complexity science to actionable targets for intervention. Lancet Psychiatry. 2021;8(11):991–1000. pmid:34627532
- 7. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of depression symptoms in US adults before and during the COVID-19 Pandemic. JAMA Netw Open. 2020;3(9):e2019686. pmid:32876685
- 8.
World Health O. Social determinants of mental health. Geneva: World Health Organization; 2014.
- 9. Alcock I, White MP, Wheeler BW, Fleming LE, Depledge MH. Longitudinal effects on mental health of moving to greener and less green urban areas. Environ Sci Technol. 2014;48(2):1247–55. pmid:24320055
- 10. Simpson J, Albani V, Bell Z, Bambra C, Brown H. Effects of social security policy reforms on mental health and inequalities: a systematic review of observational studies in high-income countries. Soc Sci Med. 2021;272:113717. pmid:33545493
- 11. Baranyi G, Di Marco MH, Russ TC, Dibben C, Pearce J. The impact of neighbourhood crime on mental health: a systematic review and meta-analysis. Soc Sci Med. 2021;282:114106. pmid:34139480
- 12. Breedvelt JJF, Tiemeier H, Sharples E, Galea S, Niedzwiedz C, Elliott I, et al. The effects of neighbourhood social cohesion on preventing depression and anxiety among adolescents and young adults: rapid review. BJPsych Open. 2022;8(4):e97. pmid:35642359
- 13. Freeman A, Tyrovolas S, Koyanagi A, Chatterji S, Leonardi M, Ayuso-Mateos JL, et al. The role of socio-economic status in depression: results from the COURAGE (aging survey in Europe). BMC Public Health. 2016;16(1):1098. pmid:27760538
- 14. Rönnblad T, Grönholm E, Jonsson J, Koranyi I, Orellana C, Kreshpaj B, et al. Precarious employment and mental health: a systematic review and meta-analysis of longitudinal studies. Scand J Work Environ Health. 2019;45(5):429–43. pmid:31165899
- 15. Lorant V, Deliège D, Eaton W, Robert A, Philippot P, Ansseau M. Socioeconomic inequalities in depression: a meta-analysis. Am J Epidemiol. 2003;157(2):98–112. pmid:12522017
- 16. Stronks K, Şekercan A, Snijder M, Lok A, Verhoeff AP, Kunst AE, et al. Higher prevalence of depressed mood in immigrants’ offspring reflects their social conditions in the host country: The HELIUS study. PLoS One. 2020;15(6):e0234006. pmid:32497057
- 17. Close C, Kouvonen A, Bosqui T, Patel K, O’Reilly D, Donnelly M. The mental health and wellbeing of first generation migrants: a systematic-narrative review of reviews. Globalization and health. 2016; 12(1):1–13.
- 18. Shah N, Walker IF, Naik Y, Rajan S, O’Hagan K, Black M, et al. National or population level interventions addressing the social determinants of mental health - an umbrella review. BMC Public Health. 2021;21(1):2118. pmid:34794401
- 19. Niedzwiedz CL, Mitchell RJ, Shortt NK, Pearce JR. Social protection spending and inequalities in depressive symptoms across Europe. Soc Psychiatry Psychiatr Epidemiol. 2016;51(7):1005–14. pmid:27138947
- 20. Ridley M, Rao G, Schilbach F, Patel V. Poverty, depression, and anxiety: Causal evidence and mechanisms. Science. 2020;370(6522):eaay0214. pmid:33303583
- 21. Thomson RM, Igelström E, Purba AK, Shimonovich M, Thomson H, McCartney G, et al. How do income changes impact on mental health and wellbeing for working-age adults? A systematic review and meta-analysis. Lancet Public Health. 2022;7(6):e515–28. pmid:35660213
- 22. Shields-Zeeman L, Smit F. The impact of income on mental health. Lancet Public Health. 2022;7(6):e486–7. pmid:35660205
- 23. Hahn RA. What is a social determinant of health? Back to basics. J Public Health Res. 2021;10(4):2324. pmid:34162174
- 24. Bank TW. World Bank Country and Lending Groups [08-06-2022]. Available from: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups
- 25. Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210. pmid:27919275
- 26.
Whitehead M, Dahlgren G. Policies and strategies to promote social equity in health. Stockholm: Institute for Future Studies. 1991.
- 27. Reeves A, McKee M, Mackenbach J, Whitehead M, Stuckler D. Introduction of a national minimum wage reduced depressive symptoms in low-wage workers: a quasi-natural experiment in the UK. Health Econ. 2017;26(5):639-55.
- 28.
Project EPHP. Quality assessment tool for quantitative studies
- 29. Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016;355:i4919. pmid:27733354
- 30. Barr B, Clayton S, Whitehead M, Thielen K, Burstrom B, Nylen L, et al. To what extent have relaxed eligibility requirements and increased generosity of disability benefits acted as disincentives for employment? A systematic review of evidence from countries with well-developed welfare systems. Journal of Epidemiology & Community Health. 2010;64(12):1106–14.
- 31. Boyd-Swan C, Herbst CM, Ifcher J, Zarghamee H. The earned income tax credit, mental health, and happiness. Journal of Economic Behavior & Organization. 2016;126:18–38.
- 32. Shields-Zeeman L, Collin DF, Batra A, Hamad R. How does income affect mental health and health behaviours? A quasi-experimental study of the earned income tax credit. J Epidemiol Community Health. 2021;75(10):929–35. pmid:33990398
- 33. Collin DF, Shields-Zeeman LS, Batra A, Vable AM, Rehkopf DH, Machen L, et al. Short-term effects of the earned income tax credit on mental health and health behaviors. Prev Med. 2020;139:106223. pmid:32735990
- 34. Spencer RA, Livingston MD, Woods-Jaeger B, Rentmeester ST, Sroczynski N, Komro KA. The impact of temporary assistance for needy families, minimum wage, and Earned Income Tax Credit on Women’s well-being and intimate partner violence victimization. Soc Sci Med. 2020;266:113355. pmid:32947076
- 35. Reeves A, McKee M, Mackenbach J, Whitehead M, Stuckler D. Introduction of a national minimum wage reduced depressive symptoms in low-wage workers: a quasi-natural experiment in the UK. Health Econ. 2017;26(5):639–55. pmid:27046821
- 36. Kronenberg C, Jacobs R, Zucchelli E. The impact of the UK national minimum wage on mental health. SSM Popul Health. 2017;3:749–55. pmid:29349261
- 37. Maxwell J, Pryce R, Wilson LB. The impact of increasing the United Kingdom national minimum wage on self-reported health. Health Econ. 2022;31(6):1167–83. pmid:35362225
- 38. Buszkiewicz JH, Hill HD, Otten JJ. Association of state minimum wage rates and health in working-age adults using the national health interview survey. Am J Epidemiol. 2021;190(1):21–30. pmid:32037444
- 39. Finkelstein A, Taubman S, Wright B, Bernstein M, Gruber J, Newhouse JP, et al. The oregon health insurance experiment: evidence from the first year. Q J Econ. 2012;127(3):1057–106. pmid:23293397
- 40. Mukhopadhyay S. The effects of Medicaid expansion on job loss induced mental distress during the COVID-19 pandemic in the US. SSM Popul Health. 2022;20:101279. pmid:36341079
- 41. Schuster ALR, Perraillon MC, Paul JJ, Leiferman JA, Battaglia C, Morrato EH. The effect of the affordable care act on women’s postpartum insurance and depression in 5 states that did not expand medicaid, 2012-2015. Med Care. 2022;60(1):22–8. pmid:34670222
- 42. Gregg P, Harkness S, Smith S. Welfare reform and lone parents in the UK. The Economic Journal. 2009;119(535):F38–65.
- 43. Harkness S. The effect of employment on the mental health of lone mothers in the UK before and after new labour’s welfare reforms. Soc Indic Res. 2015;128(2):763–91.
- 44. Barr B, Taylor-Robinson D, Stuckler D, Loopstra R, Reeves A, Whitehead M. “First, do no harm”: are disability assessments associated with adverse trends in mental health? A longitudinal ecological study. J Epidemiol Community Health. 2016;70(4):339–45. pmid:26573235
- 45. Curnock E, Leyland AH, Popham F. The impact on health of employment and welfare transitions for those receiving out-of-work disability benefits in the UK. Social Science & Medicine. 2016;162:1–10.
- 46. Katikireddi SV, Molaodi OR, Gibson M, Dundas R, Craig P. Effects of restrictions to Income Support on health of lone mothers in the UK: a natural experiment study. Lancet Public Health. 2018;3(7):e333–40. pmid:29976327
- 47. Wickham S, Bentley L, Rose T, Whitehead M, Taylor-Robinson D, Barr B. Effects on mental health of a UK welfare reform, Universal Credit: a longitudinal controlled study. Lancet Public Health. 2020;5(3):e157–64. pmid:32113519
- 48. WILLIAMS E. Unemployment, sanctions and mental health: the relationship between benefit sanctions and antidepressant prescribing. J Soc Pol. 2019;50(1):1–20.
- 49. Williams E. Punitive welfare reform and claimant mental health: The impact of benefit sanctions on anxiety and depression. Soc Policy Adm. 2020;55(1):157–72.
- 50. Jagannathan R, Camasso MJ, Sambamoorthi U. Experimental evidence of welfare reform impact on clinical anxiety and depression levels among poor women. Soc Sci Med. 2010;71(1):152–60. pmid:20434251
- 51. Rote S, Quadagno J. Depression and alcohol dependence among poor women: before and after welfare reform. Social Service Review. 2011;85(2):229–45.
- 52. Morris PA. Welfare program implementation and parents’ depression. Soc Serv Rev. 2008;82(4):579–614. pmid:22058575
- 53. Cardenas SI, Corbisiero MF, Morris AR, Saxbe DE. Associations between paid paternity leave and parental mental health across the transition to parenthood: evidence from a repeated-measure study of first-time parents in California. J Child Fam Stud. 2021;30(12):3080–94.
- 54. Doran EL, Bartel AP, Ruhm CJ, Waldfogel J. California’s paid family leave law improves maternal psychological health. Soc Sci Med. 2020;256:113003. pmid:32464413
- 55. Irish AM, White JS, Modrek S, Hamad R. Paid family leave and mental health in the U.S.: a quasi-experimental study of state policies. Am J Prev Med. 2021;61(2):182–91. pmid:34294424
- 56. Lee BC, Modrek S, White JS, Batra A, Collin DF, Hamad R. The effect of California’s paid family leave policy on parent health: A quasi-experimental study. Soc Sci Med. 2020;251:112915. pmid:32179364
- 57. Bilgrami A, Sinha K, Cutler H. The impact of introducing a national scheme for paid parental leave on maternal mental health outcomes. Health Econ. 2020;29(12):1657–81. pmid:32935432
- 58. Hewitt B, Strazdins L, Martin B. The benefits of paid maternity leave for mothers’ post-partum health and wellbeing: Evidence from an Australian evaluation. Soc Sci Med. 2017;182:97–105. pmid:28437694
- 59. Avendano M, Berkman LF, Brugiavini A, Pasini G. The long-run effect of maternity leave benefits on mental health: evidence from European countries. Soc Sci Med. 2015;132:45–53. pmid:25792339
- 60. Beuchert LV, Humlum MK, Vejlin R. The length of maternity leave and family health. Labour Economics. 2016;43:55–71.
- 61. Bütikofer A, Riise J, M. Skira M. The impact of paid maternity leave on maternal health. American Economic Journal: Economic Policy. 2021;13(1):67–105.
- 62. Grip AD, Lindeboom M, Montizaan R. Shattered dreams: the effects of changing the pension system late in the game. The Economic Journal. 2011;122(559):1–25.
- 63. Carrino L, Glaser K, Avendano M. Later retirement, job strain, and health: Evidence from the new State Pension age in the United Kingdom. Health Econ. 2020;29(8):891–912.
- 64. Kim J, Lee T-J, Kim C-S. The association between the basic old-age pension and depression of the older adults in Korea. J Prev Med Public Health. 2020;53(5):332–41. pmid:33070505
- 65. Reeves A, Clair A, McKee M, Stuckler D. Reductions in the United Kingdom’s government housing benefit and symptoms of depression in low-income households. Am J Epidemiol. 2016;184(6):421–9. pmid:27613659
- 66. Lebihan L, Mao Takongmo C-O. The impact of universal child benefits on family health and behaviours. Research in Economics. 2018;72(4):415–27.
- 67. Reinhard E, Courtin E, van Lenthe FJ, Avendano M. Public transport policy, social engagement and mental health in older age: a quasi-experimental evaluation of free bus passes in England. J Epidemiol Community Health. 2018;72(5):361–8. pmid:29352012
- 68. Hamad R, Nguyen TT, Bhattacharya J, Glymour MM, Rehkopf DH. Educational attainment and cardiovascular disease in the United States: A quasi-experimental instrumental variables analysis. PLoS Med. 2019;16(6):e1002834. pmid:31237869
- 69. Wang SS, Glied S, Williams S, Will B, Muennig PA. Impact of aeroplane noise on mental and physical health: a quasi-experimental analysis. BMJ Open. 2022;12(5):e057209. pmid:35501087
- 70. Li L, Carrino L, Reinhard E, Timmermans E, Huisman M, Claassens J, et al. Aircraft noise control policy and mental health: a natural experiment based on the Longitudinal Aging Study Amsterdam (LASA). Journal of epidemiology and community health. 2020;4.
- 71. Costello EJ, Compton SN, Keeler G, Angold A. Relationships between poverty and psychopathology: a natural experiment. JAMA. 2003;290(15):2023–9. pmid:14559956
- 72. Costello EJ, Erkanli A, Copeland W, Angold A. Association of family income supplements in adolescence with development of psychiatric and substance use disorders in adulthood among an American Indian population. JAMA. 2010;303(19):1954–60. pmid:20483972
- 73. Courtin E, Muennig P, Verma N, Riccio JA, Lagarde M, Vineis P, et al. Conditional cash transfers and health of low-income families in the us: evaluating the family rewards experiment. Health Aff (Millwood). 2018;37(3):438–46. pmid:29505381
- 74. Prause J, Dooley D, Huh J. Income volatility and psychological depression. Am J Community Psychol. 2009;43(1–2):57–70. pmid:19130213
- 75. Sareen J, Afifi TO, McMillan KA, Asmundson GJG. Relationship between household income and mental disorders: findings from a population-based longitudinal study. Arch Gen Psychiatry. 2011;68(4):419–27. pmid:21464366
- 76. Benzeval M, Judge K. Income and health: the time dimension. Soc Sci Med. 2001;52(9):1371–90. pmid:11286362
- 77. Barbaglia MG, ten Have M, Dorsselaer S, Alonso J, de Graaf R. Negative socioeconomic changes and mental disorders: a longitudinal study. J Epidemiol Community Health. 2015;69(1):55–62. pmid:25205161
- 78. Lorant V, Croux C, Weich S, Deliège D, Mackenbach J, Ansseau M. Depression and socio-economic risk factors: 7-year longitudinal population study. Br J Psychiatry. 2007;190:293–8. pmid:17401034
- 79. Wickham S, Whitehead M, Taylor-Robinson D, Barr B. The effect of a transition into poverty on child and maternal mental health: a longitudinal analysis of the UK Millennium Cohort Study. Lancet Public Health. 2017;2(3):e141–8. pmid:29253387
- 80. Thomson RM, Kopasker D, Leyland A, Pearce A, Katikireddi SV. Effects of poverty on mental health in the UK working-age population: causal analyses of the UK Household Longitudinal Study. Int J Epidemiol. 2023;52(2):512–22. pmid:36479855
- 81. Lindström M, Giordano GN. The 2008 financial crisis: Changes in social capital and its association with psychological wellbeing in the United Kingdom - A panel study. Soc Sci Med. 2016;153:71–80. pmid:26889949
- 82. Swift SL, Elfassy T, Bailey Z, Florez H, Feaster DJ, Calonico S, et al. Association of negative financial shocks during the Great Recession with depressive symptoms and substance use in the USA: the CARDIA study. J Epidemiol Community Health. 2020;74(12):995–1001. pmid:32788306
- 83. Curl A, Kearns A. Financial difficulty and mental wellbeing in an age of austerity: the experience in deprived communities. Social Policy & Society. 2014;14(2):217–40.
- 84. McInerney M, Mellor JM, Nicholas LH. Recession depression: mental health effects of the 2008 stock market crash. J Health Econ. 2013;32(6):1090–104. pmid:24113241
- 85. McCarthy B, Carter A, Jansson M, Benoit C, Finnigan R. Poverty, material hardship, and mental health among workers in three front-line service occupations. Journal of Poverty. 2018;22(4):334–54.
- 86. McKenzie SK, Imlach Gunasekara F, Richardson K, Carter K. Do changes in socioeconomic factors lead to changes in mental health? Findings from three waves of a population based panel study. J Epidemiol Community Health. 2014;68(3):253–60. pmid:24243999
- 87. Carlier BE, Schuring M, Burdorf A. Influence of an Interdisciplinary Re-employment Programme Among Unemployed Persons with Mental Health Problems on Health, Social Participation and Paid Employment. J Occup Rehabil. 2018;28(1):147–57. pmid:28397017
- 88. Claussen B. Health and re-employment in a five-year follow-up of long-term unemployed. Scand J Public Health. 1999;27(2):94–100. pmid:10421716
- 89. Claussen B, Bjørndal A, Hjort PF. Health and re-employment in a two year follow up of long term unemployed. J Epidemiol Community Health. 1993;47(1):14–8. pmid:8436885
- 90. Kessler RC, Turner JB, House JS. Unemployment, reemployment, and emotional functioning in a community sample. American Sociological Review. 1989:648–57.
- 91. Pevalin DJ, Goldberg DP. Social precursors to onset and recovery from episodes of common mental illness. Psychol Med. 2003;33(2):299–306. pmid:12622308
- 92. Strandh M. Different exit routes from unemployment and their impact on mental well-being: the role of the economic situation and the predictability of the life course. Work Emp Soc. 2000;14(3):459–79.
- 93. Morrell S, Taylor R, Quine S, Kerr C, Western J. A cohort study of unemployment as a cause of psychological disturbance in Australian youth. Soc Sci Med. 1994;38(11):1553–64. pmid:8036535
- 94. Graetz B. Health consequences of employment and unemployment: longitudinal evidence for young men and women. Soc Sci Med. 1993;36(6):715–24. pmid:8480216
- 95. Frese M, Mohr G. Prolonged unemployment and depression in older workers: a longitudinal study of intervening variables. Soc Sci Med. 1987;25(2):173–8. pmid:3660007
- 96. Lahelma E. Paid employment, unemployment and mental well-being. Psychiatria Fennica. 1992;23:131–144
- 97. Farré L, Fasani F, Mueller H. Feeling useless: the effect of unemployment on mental health in the Great Recession. IZA J Labor Econ. 2018;7(1).
- 98. Matsubayashi T, Ishikawa Y, Ueda M. Economic crisis and mental health during the COVID-19 pandemic in Japan. J Affect Disord. 2022;306:28–31. pmid:35306120
- 99. Kim S-S, Subramanian S, Sorensen G, Perry MJ, Christiani DC. Association between change in employment status and new-onset depressive symptoms in South Korea-a gender analysis. Scand J Work Environ Health. 2012;537–45.
- 100. Eisenberg-Guyot J, Peckham T, Andrea SB, Oddo V, Seixas N, Hajat A. Life-course trajectories of employment quality and health in the U.S.: a multichannel sequence analysis. Soc Sci Med. 2020;264:113327. pmid:32919256
- 101. Hoven H, Wahrendorf M, Goldberg M, Zins M, Siegrist J. Adverse employment histories, work stress and self-reported depression in the French CONSTANCES study. Eur J Public Health. 2021;31(6):1230–6. pmid:34643687
- 102. Jonsson J, Muntaner C, Bodin T, Alderling M, Rebeka R, Burström B, et al. Low-quality employment trajectories and risk of common mental disorders, substance use disorders and suicide attempt: a longitudinal study of the Swedish workforce. Scand J Work Environ Health. 2021;47(7):509–20. pmid:34397098
- 103. Brydsten A, Cederström A, Rostila M. Young people’s labour market patterns and later mental health: a sequence analysis exploring the role of region of origin for young people’s labour market trajectories and mental health. SSM Popul Health. 2020;11:100600. pmid:32548233
- 104. Ali J, Avison WR. Employment transitions and psychological distress: the contrasting experiences of single and married mothers. Journal of Health and Social Behavior. 1997;38(4):345.
- 105. Dew MA, Bromet EJ, Penkower L. Mental health effects of job loss in women. Psychol Med. 1992;22(3):751–64. pmid:1410099
- 106. Zabkiewicz D. The mental health benefits of work: do they apply to poor single mothers?. Soc Psychiatry Psychiatr Epidemiol. 2010;45(1):77–87. pmid:19367350
- 107. Zabkiewicz D, Schmidt LA. The mental health benefits of work: do they apply to welfare mothers with a drinking problem?. J Behav Health Serv Res. 2009;36(1):96–110. pmid:18797995
- 108. Breslin FC, Mustard C. Factors influencing the impact of unemployment on mental health among young and older adults in a longitudinal, population-based survey. Scand J Work Environ Health. 2003;29(1):5–14. pmid:12630430
- 109. Gallo WT, Bradley EH, Dubin JA, Jones RN, Falba TA, Teng H-M, et al. The persistence of depressive symptoms in older workers who experience involuntary job loss: results from the health and retirement survey. J Gerontol B Psychol Sci Soc Sci. 2006;61(4):S221-8. pmid:16855043
- 110. Gallo WT, Bradley EH, Siegel M, Kasl SV. Health effects of involuntary job loss among older workers: findings from the health and retirement survey. J Gerontol B Psychol Sci Soc Sci. 2000;55(3):S131-40. pmid:11833981
- 111. Salm M. Does job loss cause ill health?. Health Econ. 2009;18(9):1075–89. pmid:19634153
- 112. Ferrie JE, Shipley MJ, Stansfeld SA, Marmot MG. Effects of chronic job insecurity and change in job security on self reported health, minor psychiatric morbidity, physiological measures, and health related behaviours in British civil servants: the Whitehall II study. J Epidemiol Community Health. 2002;56(6):450–4. pmid:12011203
- 113. Magnusson Hanson LL, Chungkham HS, Ferrie J, Sverke M. Threats of dismissal and symptoms of major depression: a study using repeat measures in the Swedish working population. J Epidemiol Community Health. 2015;69(10):963–9. pmid:25934847
- 114. Blackman T, Anderson J, Pye P. Change in adult health following medical priority rehousing: a longitudinal study. J Public Health Med. 2003;25(1):22–8. pmid:12669914
- 115. Petersen J, Alexiou A, Brewerton D, Cornelsen L, Courtin E, Cummins S, et al. Impact of selective licensing schemes for private rental housing on mental health and social outcomes in Greater London, England: a natural experiment study. BMJ Open. 2022;12(12):e065747. pmid:36564110
- 116. Pevalin DJ, Reeves A, Baker E, Bentley R. The impact of persistent poor housing conditions on mental health: A longitudinal population-based study. Prev Med. 2017;105:304–10. pmid:28963007
- 117. Denary W, Fenelon A, Schlesinger P, Purtle J, Blankenship KM, Keene DE. Does rental assistance improve mental health? Insights from a longitudinal cohort study. Soc Sci Med. 2021;282:114100. pmid:34144434
- 118. Desmond M, Kimbro RT. Eviction’s fallout: housing, hardship, and health. Social Forces. 2015;94(1):295–324.
- 119. Hatch ME, Yun J. Losing your home is bad for your health: short- and medium-term health effects of eviction on young adults. Housing Policy Debate. 2020;31(3–5):469–89.
- 120. Hoke MK, Boen CE. The health impacts of eviction: Evidence from the national longitudinal study of adolescent to adult health. Soc Sci Med. 2021;273:113742. pmid:33607393
- 121. Leifheit KM, Pollack CE, Raifman J, Schwartz GL, Koehler RD, Rodriguez Bronico JV, et al. Variation in state-level eviction moratorium protections and mental health among US adults during the COVID-19 pandemic. JAMA Netw Open. 2021;4(12):e2139585. pmid:34919134
- 122. Pevalin DJ. Housing repossessions, evictions and common mental illness in the UK: results from a household panel study. J Epidemiol Community Health. 2009;63(11):949–51. pmid:19578031
- 123. Taylor MP, Pevalin DJ, Todd J. The psychological costs of unsustainable housing commitments. Psychol Med. 2007;37(7):1027–36. pmid:17224094
- 124. Alley DE, Lloyd J, Pagán JA, Pollack CE, Shardell M, Cannuscio C. Mortgage delinquency and changes in access to health resources and depressive symptoms in a nationally representative cohort of Americans older than 50 years. Am J Public Health. 2011;101(12):2293–8. pmid:22021301
- 125. Kim SH, Kim H, Joo HJ, Jeong SH, Park E-C, Jang S-I. Impact of changes in housing tenure and affordability status on depressive symptoms: Evidence from a longitudinal study. J Affect Disord. 2021;295:40–9. pmid:34403933
- 126. Fowler PJ, Henry DB, Marcal KE. Family and housing instability: Longitudinal impact on adolescent emotional and behavioral well-being. Soc Sci Res. 2015;53:364–74. pmid:26188460
- 127. Suglia SF, Duarte CS, Sandel MT. Housing quality, housing instability, and maternal mental health. J Urban Health. 2011;88(6):1105–16. pmid:21647798
- 128. Leventhal T, Brooks-Gunn J. Moving to opportunity: an experimental study of neighborhood effects on mental health. Am J Public Health. 2003;93(9):1576–82. pmid:12948983
- 129. Cooper HLF, Hunter-Jones J, Kelley ME, Karnes C, Haley DF, Ross Z, et al. The aftermath of public housing relocations: relationships between changes in local socioeconomic conditions and depressive symptoms in a cohort of adult relocaters. J Urban Health. 2014;91(2):223–41. pmid:24311024
- 130. Harvey TB John. Housing renewal and mental health: A case study. Journal of Mental Health. 2001;10(5):571–83.
- 131. Huxley P, Evans S, Leese M, Gately C, Rogers A, Thomas R, et al. Urban regeneration and mental health. Soc Psychiatry Psychiatr Epidemiol. 2004;39(4):280–5. pmid:15085329
- 132. Rose TC, Daras K, Manley J, McKeown M, Halliday E, Goodwin TL, et al. The mental health and wellbeing impact of a Community Wealth Building programme in England: a difference-in-differences study. Lancet Public Health. 2023;8(6):e403–10. pmid:37094594
- 133. Stafford M, Badland H, Nazroo J, Halliday E, Walthery P, Povall S, et al. Evaluating the health inequalities impact of area-based initiatives across the socioeconomic spectrum: a controlled intervention study of the New Deal for Communities, 2002–2008. Journal of Epidemiology and Community Health. 2014; 68(10): 979–86.
- 134. Walthery P, Stafford M, Nazroo J, Whitehead M, Dibben C, Halliday E, et al. Health trajectories in regeneration areas in England: the impact of the New Deal for Communities intervention. J Epidemiol Community Health. 2015;69(8):762–8. pmid:26085649
- 135. White J, Greene G, Farewell D, Dunstan F, Rodgers S, Lyons RA, et al. Improving mental health through the regeneration of deprived neighborhoods: a natural experiment. Am J Epidemiol. 2017;186(4):473–80. pmid:28486637
- 136. Greene G, Fone D, Farewell D, Rodgers S, Paranjothy S, Carter B, et al. Improving mental health through neighbourhood regeneration: the role of cohesion, belonging, quality and disorder. Eur J Public Health. 2020;30(5):964–6. pmid:31821478
- 137. Egan M, Katikireddi SV, Kearns A, Tannahill C, Kalacs M, Bond L. Health effects of neighborhood demolition and housing improvement: a prospective controlled study of 2 natural experiments in urban renewal. Am J Public Health. 2013;103(6):e47-53. pmid:23597345
- 138. Egan M, Kearns A, Katikireddi SV, Curl A, Lawson K, Tannahill C. Proportionate universalism in practice? A quasi-experimental study (GoWell) of a UK neighbourhood renewal programme’s impact on health inequalities. Soc Sci Med. 2016;152:41–9. pmid:26829008
- 139. Jongeneel-Grimen B, Droomers M, Kramer D, Bruggink J-W, van Oers H, Kunst AE, et al. Impact of a Dutch urban regeneration programme on mental health trends: a quasi-experimental study. J Epidemiol Community Health. 2016;70(10):967–73. pmid:27053684
- 140. Timmermans EJ, Reinhard E, Ruijsbroek A, Huisman M, Avendano M. Regeneration of deprived neighbourhoods and indicators of functioning in older adults: a quasi-experimental evaluation of the Dutch District Approach. Health Place. 2020;64:102359. pmid:32838884
- 141. Aguilar-Palacio I, Carrera-Lasfuentes P, Rabanaque MJ. Youth unemployment and economic recession in Spain: influence on health and lifestyles in young people (16–24 years old). International journal of public health. 2015;60:427–35.
- 142. Astell-Burt T, Feng X. Health and the 2008 economic recession: evidence from the United Kingdom. PLoS One. 2013;8(2):e56674. pmid:23437208
- 143. Malard L, Chastang J-F, Niedhammer I. Changes in major depressive and generalized anxiety disorders in the national French working population between 2006 and 2010. J Affect Disord. 2015;178:52–9. pmid:25795536
- 144. Lee S, Guo W-J, Tsang A, Mak ADP, Wu J, Ng KL, et al. Evidence for the 2008 economic crisis exacerbating depression in Hong Kong. J Affect Disord. 2010;126(1–2):125–33. pmid:20381157
- 145. Madianos M, Economou M, Alexiou T, Stefanis C. Depression and economic hardship across Greece in 2008 and 2009: two cross-sectional surveys nationwide. Soc Psychiatry Psychiatr Epidemiol. 2011;46(10):943–52. pmid:20614103
- 146. Economou M, Madianos M, Peppou LE, Patelakis A, Stefanis CN. Major depression in the era of economic crisis: a replication of a cross-sectional study across Greece. J Affect Disord. 2013;145(3):308–14. pmid:22939388
- 147. Modrek S, Hamad R, Cullen MR. Psychological well-being during the great recession: changes in mental health care utilization in an occupational cohort. Am J Public Health. 2015;105(2):304–10. pmid:25521885
- 148. Buffel V, Van de Velde S, Bracke P. The mental health consequences of the economic crisis in Europe among the employed, the unemployed, and the non-employed. Soc Sci Res. 2015;54:263–88. pmid:26463548
- 149. Drydakis N. The effect of unemployment on self-reported health and mental health in Greece from 2008 to 2013: a longitudinal study before and during the financial crisis. Soc Sci Med. 2015;128:43–51. pmid:25589031
- 150. Bartoll X, Palència L, Malmusi D, Suhrcke M, Borrell C. The evolution of mental health in Spain during the economic crisis. Eur J Public Health. 2014;24(3):415–8. pmid:24367067
- 151. Gili M, Roca M, Basu S, McKee M, Stuckler D. The mental health risks of economic crisis in Spain: evidence from primary care centres, 2006 and 2010. Eur J Public Health. 2013;23(1):103–8. pmid:23132877
- 152. Barr B, Kinderman P, Whitehead M. Trends in mental health inequalities in England during a period of recession, austerity and welfare reform 2004 to 2013. Soc Sci Med. 2015;147:324–31. pmid:26623942
- 153. Nour S, Labonté R, Bancej C. Impact of the 2008 global financial crisis on the health of Canadians: repeated cross-sectional analysis of the Canadian Community Health Survey, 2007–2013. Journal of epidemiology and community health. 2017; 71(4):336–43.
- 154. Cherrie M, Curtis S, Baranyi G, Cunningham N, Dibben C, Bambra C, et al. A data linkage study of the effects of the great recession and austerity on antidepressant prescription usage. Eur J Public Health. 2021;31(2):297–303. pmid:33550373
- 155. Villarroel N, MacFarlane A, Roura M, Basogomba A, Bradley C, LeMaster JW, et al. The impact of economic recession on the health of migrant fathers over time: results from the Growing up in Ireland longitudinal study. BMC Public Health. 2022;22(1):166. pmid:35073892
- 156. Gotsens M, Malmusi D, Villarroel N, Vives-Cases C, Garcia-Subirats I, Hernando C, et al. Health inequality between immigrants and natives in Spain: the loss of the healthy immigrant effect in times of economic crisis. Eur J Public Health. 2015;25(6):923–9. pmid:26136466
- 157. Rahmqvist M, Carstensen J. Trend of psychological distress in a Swedish population from 1989 to 1995. Scand J Soc Med. 1998;26(3):214–22. pmid:9768452
- 158. Ruijsbroek A, Wong A, den Hertog F, Droomers M, van den Brink C, Kunst AE, et al. Do inhabitants profit from integrating a public health focus in urban renewal programmes? A dutch case study. PLoS One. 2022;17(6):e0270367. pmid:35749511
- 159. Mair C, Diez Roux AV, Golden SH, Rapp S, Seeman T, Shea S. Change in neighborhood environments and depressive symptoms in New York City: The multi-ethnic study of atherosclerosis. Health Place. 2015;32:93–8. pmid:25665936
- 160. Astell-Burt T, Feng X, Kolt GS, Jalaludin B. Does rising crime lead to increasing distress? Longitudinal analysis of a natural experiment with dynamic objective neighbourhood measures. Social science & medicine (1982). 2015;138:68–73.
- 161. Dustmann C, Fasani F. The effect of local area crime on mental health. The Economic Journal. 2015;126(593):978–1017.
- 162. Cruwys T, Alexander Haslam S, Dingle GA, Jetten J, Hornsey MJ, Desdemona Chong EM, et al. Feeling connected again: interventions that increase social identification reduce depression symptoms in community and clinical settings. J Affect Disord. 2014;159:139–46. pmid:24679402
- 163. McGale N, McArdle S, Gaffney P. Exploring the effectiveness of an integrated exercise/CBT intervention for young men’s mental health. Br J Health Psychol. 2011;16(3):457–71. pmid:21722270
- 164. Murayama Y, Ohba H, Yasunaga M, Nonaka K, Takeuchi R, Nishi M, et al. The effect of intergenerational programs on the mental health of elderly adults. Aging Ment Health. 2015;19(4):306–14. pmid:25010219
- 165. Watanabe R, Kondo K, Saito T, Tsuji T, Hayashi T, Ikeda T, et al. Change in municipality-level health-related social capital and depressive symptoms: ecological and 5-year repeated cross-sectional study from the JAGES. Int J Environ Res Public Health. 2019;16(11):2038. pmid:31181718
- 166. Heshmati A, Honkaniemi H, Juárez SP. The effect of parental leave on parents’ mental health: a systematic review. Lancet Public Health. 2023;8(1):e57–75. pmid:36603912
- 167. Paul KI, Moser K. Unemployment impairs mental health: Meta-analyses. Journal of Vocational Behavior. 2009;74(3):264–82.
- 168. Murphy GC, Athanasou JA. The effect of unemployment on mental health. J Occupat & Organ Psyc. 1999;72(1):83–99.
- 169.
Keith MG, Harms PD, Long AC. Worker health and well-being in the gig economy: A proposed framework and research agenda. Entrepreneurial and Small Business Stressors, Experienced Stress, and Well-Being. 2020;18:1–33.
- 170. Nagy E, Moore S. Social interventions: An effective approach to reduce adult depression?. J Affect Disord. 2017;218:131–52. pmid:28472703
- 171. Wickramaratne PJ, Yangchen T, Lepow L, Patra BG, Glicksburg B, Talati A, et al. Social connectedness as a determinant of mental health: A scoping review. PLoS One. 2022;17(10):e0275004. pmid:36228007
- 172. Cunningham S, Hudson CC, Harkness K. Social media and depression symptoms: a meta-analysis. Res Child Adolesc Psychopathol. 2021;49(2):241–53. pmid:33404948
- 173. Dejonckheere E, Bastian B, Fried EI, Murphy SC, Kuppens P. Perceiving social pressure not to feel negative predicts depressive symptoms in daily life. Depress Anxiety. 2017;34(9):836–44. pmid:28499066
- 174. Langellier BA, Yang Y, Purtle J, Nelson KL, Stankov I, Diez Roux AV. Complex systems approaches to understand drivers of mental health and inform mental health policy: a systematic review. Adm Policy Ment Health. 2019;46(2):128–44. pmid:29995289
- 175. Hewitt G, Sims S, Harris R. The realist approach to evaluation research: an introduction. International Journal of Therapy and Rehabilitation. 2012;19(5):250–9.
- 176. Alegría M, NeMoyer A, Falgàs Bagué I, Wang Y, Alvarez K. Social determinants of mental health: where we are and where we need to go. Curr Psychiatry Rep. 2018;20(11):95. pmid:30221308
- 177. Sampson L, Galea S. An argument for the foundations of population mental health. Front Psychiatry. 2018;9:600. pmid:30510524
- 178. Chisholm D, Sweeny K, Sheehan P, Rasmussen B, Smit F, Cuijpers P, et al. Scaling-up treatment of depression and anxiety: a global return on investment analysis. Lancet Psychiatry. 2016;3(5):415–24. pmid:27083119