Table 5.

Characteristics of studies included in review relating job quality and security, deprivation and socioeconomic status and mental health outcomes, 2004–2014

Study	Setting	Study design	N Year Age	Socioeconomic determinants	Mental health outcomes	Associations/Effects	Strengths	Limitations
[106]	National population sample, Finland	Cohort	3449 31 y	Individual-level indicators Psychosocial job quality and Security	Psychological Well-being Mental health distress caseness (HSCL-25) Self-reports of GP	The precarious workers have more distress symptoms in comparison with permanent workers. No differences in doctor-diagnosed/treated illnesses between precarious and permanent workers.	It measures mental health and correlates with self-reports of doctor diagnosed/treated illnesses. Temporal order of exposures and confounders affected all participants at the same time producing stronger causal conclusions.	Cannot make differential analysis of health-based selection. The results and recommendations should not be generalized to other cohorts.
[107]	Regional population sample, Northern Sweden	Cohort	1071 30–42y	Individual-level indicators Psychosocial job security	Psychological Well-being Self-rated health, sleep quality and mental health	The adverse effects of job insecurity on health are present on both permanent and temporary employees.	The study has a follow-up design. Temporal order of exposures affected all participants at the same time producing stronger causal conclusions.	The results and recommendations should not be generalized to other cohorts.
[108]	Community sample of workers from private organization, Italy	Cross-sectional	1236 (2010–2011)	Individual-level indicators Psychosocial job quality and Security	Psychological Well-being Mental health distress (GHQ12)	Job stress fully mediated the relationship between fear of the crisis and mental health of the workers.	Large sample and uses a well validated scale for detection of mental distress.	Its cross-sectional design removes the possibility of causal inference. Possible response bias since those with mental distress may perceive and rate the same work environment more stressful than those without mental distress.
[109]	National Population sample, England, UK	Cross-sectional	2603 20–55 y	Individual-level indicators Employment Status Psychosocial job quality	Common Mental Disorders CIS-R interview: Common Mental Disorders (CMD)	The prevalence of mental disorders among unemployed (33.1 %) was greater than in employed (12.9 %; OR 3.34, 95 % CI 2.06–5.42, p < 0.001). Results were similar for those respondents in the poorest quality jobs.	Uses a well validated scale for detection of common mental disorders.	Its cross-sectional design removes the possibility of causal inference. Possible response bias since those with mental illnesses may perceive and rate the same work environment more negatively than those without a disorder.
[110]	National working population sample, UK	Cross-sectional	3581 (2007) 16–64y	Individual-level indicators Psychosocial job security Indebtedness	Common Mental Disorders Depression	Risk of depression is greater for poor job security (OR = 1.58, 95 %; CI:1.22–2.06). Adj for age and sex, job insecurity (OR = 1.86, 95 % CI:1.47–2.35) and debt (OR = 2.17, 95 % CI:1.58–2.98) were independently associated.	Large representative sample.	Its cross-sectional design removes the possibility of causal inference: job insecurity may be more frequently reported by people rendered pessimistic by a mood disorder.
[111]	National population sample, USA	Cohort	34,653 (2001–02; 04–05) ≥20 y	Individual-level indicators Household income Socioeconomic inequalities	Common Mental Disorders Substance use disorders (AUDADIS-IV)	A decrease in household income during the 2 time points was associated with an increased risk of incident mood, anxiety, or substance use disorders (adj OR = 1.30; 99 % CI:1.06–1.60)	Nationally representative sample and strong associations. Temporal order of exposures produces stronger causal conclusions.	Unable to adjust for physical health conditions that may be potential confounders.
[112]	National population sample, New Zealand	Cohort	15,340 (2002–2004/05) >25 y	Individual-level indicators Total wealth Socioeconomic inequalities	Psychological Well-being Mental health distress (Kessler-10)	High psychological distress linked to lowest wealth quintile compared with the highest (OR 3.06, 95 % CI 2.68 to 3.50). Adj for age and sex did not alter the relationship; adj for income and area deprivation attenuated the OR to 1.73 (95 % CI 1.48 to 2.04); adj baseline health status reduced the OR to 1.45 (95 % CI 1.23 to 1.71).	Strong associations between inequalities in wealth and psychological distress. Temporal order of exposures and confounders affected all participants at the same time producing stronger causal conclusions.	The socioeconomic position at baseline was not controlled. The results and recommendations should not be generalized to other cohorts.
[113]	National population sample, Britain, UK	Cohort	8185 (1991) (2003)	Individual-level indicators Indebtedness housing payment problems	Psychological Well-being Mental health distress caseness (GHQ-12)	Housing payment problems and debts have significant detrimental effects on mental Well-being. The sizes of these effects are in addition to and larger in magnitude than those associated with financial hardship.	Temporal order of exposures, confounders, and the outcome under consideration affected all participants at the same time producing stronger causal conclusions.	Generalizing findings may be reasonably limited to the UK’s welfare system in regard to housing payment problems. The results and recommendations should not be generalized to other cohorts.
[114]	Community sample, Detroit, USA	Cohort	1547 (2008) (2010)	Individual-level indicators Home foreclosure Financial hardship	Common Mental Disorders Major depression (PHQ-9) Generalized anxiety disorder (GAD-7)	Foreclosure was associated with an increased rate of major depression [incidence density ratio (IDR) 2.4, 95 %; CI:1.6–3.6] and GAD (IDR 1.9, 95 %; CI:1.4–2.6)	Establishes longitudinal associations between home foreclosure and common mental disorders producing stronger causal conclusions.	The sample is limited to a longitudinal cohort of pre-dominantly African-American adults. Because mental health problems are common among individuals at risk of foreclosure, the observed associations may result, in part, from pre-existing psychopathology.
[115]	Community sample, Wales, UK	Cross-sectional	88,623 (2003/04–2010) 18–74 y	Individual-level indicators Area income deprivation Socioeconomic inequalities	Psychological Well-being Mental health distress (MHI-5)	High neighbourhood income inequality was associated with better mental health in low-deprivation neighbourhoods (P = 0.036). Income inequality at regional level was significantly associated with poorer mental health (P = 0.012).	Uses a continuous measure of mental health symptoms. Large sampling fraction.	No data were available on individual income. Its cross-sectional design removes the possibility of causal inference.
[116]	Community sample, France	Cohort	1103 (1991–2009) 22–35 y	Individual-level indicators Socioeconomic status Level of education	Substance-Disorders tobacco, cannabis use, other illegal drug use	Low socioeconomic status was linked with higher rates of tobacco smoking [OR = 2.11, 95 % CI 1.51–2.96], cannabis use [OR = 1.75, 95 % 1.20–2.55], problematic cannabis use [OR = 2.44, 95 % CI 1.38–4.30] and other illegal drugs [OR = 2.27, 95 % CI 1.11–4.65].	Relatively large community sample of young adults. Longitudinal measures of family and juvenile characteristics obtained independently of participants’ reports of substance-use	The research focused only young adults whose parents worked in a large national company and were part of an ongoing epidemiological study. Other variables that can act as confounders were not controlled: family and peer characteristics.
[117]	National population sample, England, UK	Cross-sectional	7461 (2007) 35–54 y	Individual-level indicators Indebtedness	Suicidal Behaviours Suicidal ideation	Those in debt were twice as likely to think about suicide after controlling for socio-demographic, economic and lifestyle factors.	Representative sample. Strong association between suicidal thoughts and being in debt.	No causal inference can be made due to the cross-sectional nature of the study.