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Precarious employment and mental health across European welfare states: a gender perspective

International Archives of Occupational and Environmental Health (2022)Cite this article

Abstract

Objective

The aim of this article was to examine the relationship between precarious employment (PE), welfare states (WS) and mental health in Europe from a gender perspective.

Methods

Data were derived from the European Working Conditions Survey 2015. PE was measured through the Employment Precariousness Scale for Europe (EPRES-E), validated for comparative research in 22 European countries, and categorized into quartiles. Countries were classified into Continental, Anglo-Saxon, Scandinavian, Southern and Central-Eastern WS. Mental health was assessed through the WHO-5 Well-Being Index and dichotomized into poor and good mental health. In a sample of 22,555 formal employees, we performed gender-stratified multi-level logistic regression models.

Results

Results showed greater prevalences of PE and poor mental health among women. However, the association between them was stronger among men. Cross-country differences were observed in multi-level regressions, but the interaction effect of WS was only significant among women. More precisely, Central-Eastern WS enhanced the likelihood of poor mental health among women in high precarious employment situations (quartiles 3 and 4).

Conclusions

These findings suggest the interaction between contextual and individual factors in the production of mental health inequalities, both within and across countries. They also call for the incorporation of gender-sensitive welfare policies if equitable and healthy labor markets are to be achieved in Europe.

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Fig. 1

Notes

  1. Operationalization according to the wage levels defined by the Organisation for Economic Co-operation and Development (OECD, 2020b).

References

  • Alsos K, Nergaard K, Van Heuvel A (2019) Collective bargaining as a tool to ensure a living wage. Experiences from the Nordic countries. Transf Eur Rev Labour Res 25(3):351–365

    Google Scholar 

  • Arts W, Gelissen J (2010) Models of the welfare state. In: Leibfried S, Lewis J, Obinger H, Pierson C (eds) The Oxford handbook of the welfare state. Oxford University Press, Oxford

    Google Scholar 

  • Auer P, Cazes S (2003) Employment stability in an age of flexibility: evidence from industrialized countries. International Labour Organization, Geneva

    Google Scholar 

  • Bambra C, Eikemo TA (2009) Welfare state regimes, unemployment and health: a comparative study of the relationship between unemployment and self-reported health in 23 European countries. J Epidemiol Community Health 63(2):92–98

    CAS  Google Scholar 

  • Bardasi E, Francesconi M (2004) The impact of atypical employment on individual wellbeing: evidence from a panel of British workers. Soc Sci Med 58:1671–1688

    Google Scholar 

  • Barnett R, Hyde J (2001) Women, men, work, and family: an expansionist theory. Am Psychol 56(10):781–796

    CAS  Google Scholar 

  • Benach J, Vives A, Amable M, Vanroelen C, Tarafa G, Muntaner C (2014) Precarious employment: understanding an emerging social determinant of health. Annu Rev Public Health 35:229–253

    CAS  Google Scholar 

  • Benach J, Vives A, Tarafa G, Delclos C, Muntaner C (2016) What should we know about precarious employment and health in 2025? Framing the agenda for the next decade of research. Int J Epidemiol 45(1):232–238

    CAS  Google Scholar 

  • Bergqvist K, Yngwe M, Lundberg O (2013) Understanding the role of welfare state characteristics for health and inequalities—an analytical review. BMC Public Health 13(1):1–20

    Google Scholar 

  • Bodin T, Çağlayan Ç, Garde AH, Gnesi M, Jonsson J, Kiran S, Julià M (2020) Precarious employment in occupational health—an omega-net working group position paper. Scand J Work Environ Health 46(3):321–329

    Google Scholar 

  • Briggs A (1961) The welfare state in historical perspective. Eur J Sociol 2(2):221–258

    Google Scholar 

  • Campos-Serna J, Ronda-Pérez E, Artazcoz L, Moen BE, Benavides FG (2013) Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review. Int J Equity Health 12(1):1–18

    Google Scholar 

  • Cerami A, Vanhuysse P (2009) Post-communist welfare pathways: theorizing social policy transformations in Central and Eastern Europe. Palgrave Macmillan Ltd, London

    Google Scholar 

  • Christofides LN, Polycarpou A, Vrachimis K (2013) Gender wage gaps, “sticky floors” and “glass ceilings” in Europe. Labour Econ 21:86–102

    Google Scholar 

  • Chung H, Muntaner C (2006) Political and welfare state determinants of infant and child health indicators: an analysis of wealthy countries. Soc Sci Med 63(3):829–842

    Google Scholar 

  • Chung H, Muntaner C (2007) Welfare state matters: a typological multilevel analysis of wealthy countries. Health Policy 80(2):328–339

    Google Scholar 

  • Dahl E, Van der Wel KA (2013) Educational inequalities in health in European welfare states: a social expenditure approach. Soc Sci Med 81:60–69

    Google Scholar 

  • Daly M (2001) Globalization and the Bismarckian Welfare States. In: Skyes R, Prior B, Palier P (eds) Globalization and European Welfare States: Challenges and Change. Palgrave Macmillan Ltd, New York

    Google Scholar 

  • Daly M (2020) gender inequality and welfare states in Europe. Edward Elgard Publishing, Cheltenham

    Google Scholar 

  • De Moortel D, Vandenheede H, Vanroelen C (2014) Contemporary employment arrangements and mental well-being in men and women across Europe: a cross-sectional study. Int J Equity Health 13(1):90

    Google Scholar 

  • De Witte H, Pienaar J, De Cuyper N (2016) Review of 30 years of longitudinal studies on the association between job insecurity and health and well-being: is there causal evidence? Aust Psychol 51(1):18–31

    Google Scholar 

  • Eikemo TA, Bambra C (2008) The welfare state: a glossary for public health. J Epidemiol Community Health 62(1):3–6

    CAS  Google Scholar 

  • Esping-Andersen G (1990) The three worlds of welfare capitalism. Princeton University Press, Princeton

    Google Scholar 

  • Eurofound (2020) European working conditions survey. Available at: https://www.eurofound.europa.eu/surveys/european-working-conditions-surveys-ewcs

  • Farina E, Green C, McVicar D (2020) Zero hour contracts and their growth. Br J Ind Relat 58(3):507–531

    Google Scholar 

  • Fenger H (2007) Welfare regimes in Central and Eastern Europe: incorporating post-communist countries in welfare regime typology. Contemp Issues Ideas Soc Sci 3(2):1–20

    Google Scholar 

  • Ferrera M (1999) The “Southern model” of welfare in social Europe. J Eur Soc Policy 6:17–37

    Google Scholar 

  • Fritzell J, Hvinden B, Kautto M, Kvist J, Uusitalo H (2005) Nordic welfare states in the European context. Routledge, London

    Google Scholar 

  • Gevaert J, Van Aerden K, De Moortel D, Vanroelen C (2020) Employment quality as a health determinant: empirical evidence for the waged and self-employed. Work Occup 48(2):146–183

    Google Scholar 

  • Hanson S, Pratt G (1991) Job search and the occupational segregation of women. Ann Assoc Am Geogr 81(2):229–253

    Google Scholar 

  • Heisig J, Schaeffer M (2019) Why You should always include a random slope for the lower-level variable involved in a cross-level interaction. Eur Sociol Rev 35(2):258–279

    Google Scholar 

  • Hox J, Moerbeek M, Van de Schoot R (2017) Multilevel analysis: techniques and applications, 3rd edn. Routledge, New York

    Google Scholar 

  • International Labour Organization (2018) Global Wage Report 2018/19 What lies behind gender pay gaps. International Labour Organization, Geneva

    Google Scholar 

  • Jonsson J, Vives A, Benach J, Kjellberg K, Selander J, Johansson G, Bodin T (2019) Measuring precarious employment in Sweden: translation, adaptation and psychometric properties of the Employment Precariousness Scale (EPRES). BMJ Open 9(9):e029577

    Google Scholar 

  • Julià M, Vives A, Tarafa G, Benach J (2017) Changing the way we understand precarious employment and health: precarisation affects the entire salaried population. Saf Sci 100:66–73

    Google Scholar 

  • Kalleberg A (2018) Precarious lives: job insecurity and well-being in rich democracies. Polity Press, Cambridge

    Google Scholar 

  • Kim IH, Muntaner C, Vahid Shahidi F, Vives A, Vanroelen C, Benach J (2012) Welfare states, flexible employment, and health: a critical review. Health Policy 104(2):99–127

    Google Scholar 

  • Koranyi I, Jonsson J, Rönnblad T, Stockfelt L, Bodin T (2018) Precarious employment and occupational accidents and injuries-a systematic review. Scand J Work Environ Health 44(4):341–350

    Google Scholar 

  • Korpi W (2016) The democratic class struggle. Routledge, London

    Google Scholar 

  • Korpi W, Ferrarini T, Englund S (2013) Women’s opportunities under different family policy constellations: gender, class and inequality tradeoffs in western countries re-examined. Soc Polit Int Stud Gend State Soc 20:1–40

    Google Scholar 

  • Kovačević J, Šehić D (2015) The pursuit of a remedy for gender inequality in wider Europe: comparison of policies and indices in the EU, Nordic Countries, and sout east Europe. Econ Ann 60(204):127–156

    Google Scholar 

  • Kreshpaj B, Orellana C, Burström B, Davis L, Hemmingsson T, Johansson G, Bodin T (2020) What is precarious employment? A systematic review of definitions and operationalizations from quantitative and qualitative studies. Scand J Work Environ Health 46(3):235–247

    Google Scholar 

  • Kuttner R (2018) Can democracy survive global capitalism? Norton, New York

    Google Scholar 

  • Lewis J (1992) Gender and the development of welfare regimes. Norton, New York

    Google Scholar 

  • Li C (2013) Little’s test of missing completely at random. Stand Genom Sci 13(4):795–809

    Google Scholar 

  • Lokar S (2000) The situation of women in Eastern Europe: five theses. Labour Force Eastern Eur 66:66–78

    Google Scholar 

  • Marmot M, Wilkinson R (2005) Social determinants of health. Oxford University Press, Oxford

    Google Scholar 

  • Menéndez M, Benach J, Muntaner C, Amable M, O’Campo P (2007) Is precarious employment more damaging to women’s health than men’s? Soc Sci Med 64(4):776–781

    Google Scholar 

  • Mensah A, Adjei N (2020) Work-life balance and self-reported health among working adults in Europe: a gender and welfare state regime comparative analysis. BMC Public Health 20:1052

    Google Scholar 

  • Muñoz-Bustillo R, Fernández-Macías E, Antón J, Esteve F (2009) Indicators of job quality in the European Union. European Parliament, Brussels

    Google Scholar 

  • Muntaner C (2016) Global precarious employment and health inequalities: working conditions, social class or precariat? Cad Saude Publ 32:e00162215

    Google Scholar 

  • Muntaner C, Chung H, Solar O, Santana V, Castedo A, Benach J, E N (2010) A macro-level model of employment relations and health inequalities. Int J Health Serv 40(2):215–221

    Google Scholar 

  • Muntaner C, Borrell C, Ng E, Chung H, Espelt A, Rodríguez-Sanz M, O’Campo P (2011) Politics, welfare regimes, and population health: controversies and evidence. Sociol Health Illn 33(6):946–964

    Google Scholar 

  • Naldini M (2004) The family in the Mediterranean welfare states. Routledge, New York

    Google Scholar 

  • Navarro V, Shi L (2001) The political context of social inequalities and health. Int J Health Serv 31(1):1–21

    CAS  Google Scholar 

  • Navarro V, Muntaner C, Borrell C, Benach J, Quiroga Á, Rodríguez-Sanz M, Pasarín MI (2006) Politics and health outcomes. The Lancet 368(9540):1033–1037

    Google Scholar 

  • O’Campo P, Eaton WW, Muntaner C (2004) Labor market experience, work organization, gender inequalities and health status: results from a prospective analysis of US employed women. Soc Sci Med 58(3):585–594

    Google Scholar 

  • Padrosa E, Belvis F, Benach J, Julià M (2021a) Measuring precarious employment in the European working conditions survey: psychometric properties and construct validity in Spain. Qual Quant 55(2):543–562

    Google Scholar 

  • Padrosa E, Bolíbar M, Julià M, Benach J (2021b) Comparing precarious employment across countries: measurement invariance of the employment precariousness scale for Europe (EPRES-E). Soc Indic Res 154:893–915

    Google Scholar 

  • Pascall G, Manning N (2000) Gender and social policy: comparing welfare states in Central and Eastern Europe and the former Soviet Union. J Eur Soc Policy 10(3):240–266

    Google Scholar 

  • Piketty T (2015) About capital in the twenty-first century. Am Econ Rev 105(5):48–53

    Google Scholar 

  • Plomien A (2006) Women and the labor market in Poland: from socialism to capitalism. Globalization, uncertainty and women’s careers: an international comparison. Edward Elgar Publishing, Cheltenham

    Google Scholar 

  • Pollert A (2003) Women, work and equal opportunities in post-communist transition. Work Employ Soc 17(2):331–357

    Google Scholar 

  • Puig-Barrachina V, Vanroelen C, Vives A, Martínez J, Muntaner C, Levecque K, Louckx F (2014) Measuring employment precariousness in the European working conditions survey: the social distribution in Europe. Work 49(1):143–161

    Google Scholar 

  • Rodgers G (1989) Precarious work in Western Europe. In: Rodgers G, Rodgers J (eds) Precarious jobs in labour market regulation: the growth of atypical employment in Western Europe. International Institute for Labour Studies, Geneva, pp 1–16

    Google Scholar 

  • Rönnblad T, Grönholm E, Jonsson J, Koranyi I, Orellana C, Kreshpaj B, Bodin T (2019) Precarious employment and mental health: a systematic review and meta-analysis of longitudinal studies. Scand J Work Environ Health 45(5):429–443

    Google Scholar 

  • Rosenfield S, Mouzon D (2013) Gender and mental health. In: Aneshensel C, Phelan J, Bierman A (eds) Handbook of the sociology of mental health. Springer, Dordrecht

    Google Scholar 

  • Rubery J, Fagan C (1995) Gender segregation in societal context. Work Employ Soc 9(2):213–240

    Google Scholar 

  • Shahidi F, De Moortel D, Muntaner C, Davis O, Siddiqi A (2016a) Do flexicurity policies protect workers from the adverse health consequences of temporary employment? A cross-national comparative analysis. SSM-Popul Health 2:674–682

    Google Scholar 

  • Shahidi F, Siddiqi A, Muntaner C (2016b) Does social policy moderate the impact of unemployment on health? A multilevel analysis of 23 welfare states. Eur J Public Health 26(6):1017–1022

    Google Scholar 

  • StataCorp (2015) Stata statistical software: release 14. StataCorp LP, College Station

    Google Scholar 

  • Topp C, Østergaard S, Søndergaard S, Bech P (2015) The WHO-5 well-being index: a systematic review of the literature. Psychother Psychosom 84:167–176

    Google Scholar 

  • Utzet M, Valero E, Mosquera I, Martin U (2020) Employment precariousness and mental health—understanding a complex reality: a systematic review. Int J Occup Med Environ Health 33(5):569–598

    Google Scholar 

  • Valero E, Martin U, Bacigalupe A, Utzet M (2021) The impact of precarious jobs on mental health: a gender-sensitive literature review. Int Arch Occup Environ Health 94(4):577–589. https://doi.org/10.1007/s00420-020-01605-7

    Article  Google Scholar 

  • Van Aerden K, Puig-Barrachina V, Bosmans K, Vanroelen C (2016) How does employment quality relate to health and job satisfaction in Europe? A typological approach. Soc Sci Med 158:132–140

    Google Scholar 

  • Virtanen M, Kivimäki M, Joensuu M, Virtanen P, Elovainio M, Vahtera J (2005) Temporary employment and health: a review. Int J Epidemiol 34(3):610–622

    Google Scholar 

  • Vives A, Amable M, Ferrer M, Moncada S, Llorens C, Muntaner C, Benach J (2010) The employment precariousness scale (EPRES): psychometric properties of a new tool for epidemiological studies among waged and salaried workers. Occup Environ Med 67(8):548–555

    Google Scholar 

  • Vives A, González F, Moncada S, Llorens C, Benach J (2015) Measuring precarious employment in times of crisis: the revised employment precariousness scale (EPRES) in Spain. Gac Sanit 29(5):379–382

    Google Scholar 

  • Vives A, González-López F, Solar O, Bernales-Baksai P, González MJ, Benach J (2017) Precarious employment in Chile: psychometric properties of the chilean version of Employment Precariousness Scale in private sector workers. Cad Saude Publ 33:e00156215

    Google Scholar 

  • Vives A, Benmarhnia T, González F, Benach J (2020) The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: results from a national survey of Chilean workers. PLoS ONE 15(9):e0238401

    CAS  Google Scholar 

  • Vosko L, MacDonald M, Campbell I (2009) Gender and the contours of precarious employment. Routledge, New York

    Google Scholar 

  • Weiner E (2010) Market dreams: gender, class, and capitalism in the Czech Republic. University of Michigan Press, Michigan

    Google Scholar 

  • White I, Royston P, Wood A (2011) Multiple imputation using chained equations: Issues and guidance for practice. Stat Med 30:377–399

    Google Scholar 

  • WHO Commission on Social Determinants of Health (2008) Closing the Gap in a Generation: Health Equity through Action on the Social Determinants of Health: Commission on Social Determinants of Health Final. Report World Health Organization, Geneva

    Google Scholar 

  • World Health Organization (1998) Wellbeing measures in primary health care/the depcare project. WHO Regional Office for Europe, Copenhagen

    Google Scholar 

  • Young M (2010) Gender differences in precarious work settings. Ind Relat 65(1):74–97

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank Jessie Gevaert and Mireia Bolíbar for their helpful comments on earlier versions of the manuscript, as well as for their methodological advice.

Funding

The research leading to these results was supported by the Spanish Ministry of Science, Innovation and Universities under grant agreement Nº CSO2016-79103R (AEI/FEDER, UE), and by the ICREA Academia program, which financially supports the work of JB. Funders were not involved in the study design, collection, analysis and interpretation of data, in the writing of the manuscript, and in the decision to submit it for publication.

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Authors and Affiliations

  1. ESIMar (Mar Nursing School), Parc de Salut Mar, Universitat Pompeu Fabra-Affiliated, Mar Campus, 08003, Barcelona, Spain

    Eva Padrosa & Mireia Julià

  2. SDHEd (Social Determinants and Health Education Research Group), IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain

    Eva Padrosa, Christophe Vanroelen, Joan Benach & Mireia Julià

  3. Research Group On Health Inequalities, Environment, and Employment Conditions Network (GREDS-EMCONET), Department of Political and Social Sciences, Universitat Pompeu Fabra, Barcelona, Spain

    Eva Padrosa, Joan Benach & Mireia Julià

  4. Interface Demography (ID), Department of Sociology, Vrije Universiteit Brussel, Barcelona, Spain

    Christophe Vanroelen

  5. Faculty of Nursing, University of Toronto, Toronto, Canada

    Carles Muntaner

  6. Dalla Lana School of Public Health, University of Toronto, Toronto, Canada

    Carles Muntaner

  7. Transdisciplinary Research Group On Socioecological Transitions (GinTrans2), Autonomous University of Madrid, Madrid, Spain

    Joan Benach

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  1. Eva Padrosa
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by EP. The first draft of the manuscript was written by EP and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Eva Padrosa.

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Appendices

Appendix

Appendix 1 Operationalization of the EPRES-E structure.

  Indicator Operationalisation Response options
Temporariness Duration of current contract Combination of: (a) what type of contract do you have; b) what is the duration of your current contract? 0. Permanent contract
1. Temporary, >  = 1 year
2. Temporary, no exact duration
3. Temporary, 6–11 months
4. Temporary, < 6 months
Tenure How many years have you been in your company or organization? 0. More than 10 years
1. 10–5 years
2. 5–3 years
3. 3–1 year
4. Less than 1 year
Disempowerment Trade unions Does a trade union, works council or a similar committee representing employees exist at your organization? 0. Yes
1. No
2. Don’t know
Meetings Does a regular meeting in which employees can express their views about what is happening in the organization exist at your organization? 0. Yes
1. No
2. Don’t know
Vulnerability Respect of boss Your immediate boss respects you as a person 0. Strongly agree
1. Tend to agree
2. Neither agree nor disagree
3. Tend to disagree
4. Strongly disagree
Fair treatment You are treated fairly at your workplace 0. Always
1. Most of the time
2. Sometimes
3. Rarely
4. Never
Exercise of rights Break when you need it You can take a break when you wish 0. Always
1. Most of the time
2. Sometimes
3. Rarely
4. Never
Hours off for personal matters Would you say that for you arranging to take an hour or two off during working hours to take care of personal or family matters is… 0. Very easy
1. Fairly easy
2. Fairly difficult
3. Very difficult
Uncertain working times Schedule unpredictability Do changes to your working time arrangements occur regularly? If yes, how long before are you informed about these changes? 0. No
1. Yes, several weeks in advance
2. Yes, several days in advance
3. Yes, the day before
4. Yes, the same day
Work at short notice How often have you been requested to come into work at short notice? 0. Never
1. Less often
2. Several times a month
3. Several times a week
4. Daily
Working times regularity Combination of: do you work (a) the same number of hours every day; b) the same number of days every week; c) the same number of hours every week; (d) fixed starting and finishing times? 0. Very high (yes on all)
1. High (no on at least one)
2. Medium (no on at least two)
3. Low (no on at least three)
4. Very low (no on all)
Wages Net earnings per month Net monthly earnings from your main paid job 0. High earnings (more than 1.5 of the median population)Footnote

Operationalization according to the wage levels defined by the Organisation for Economic Co-operation and Development (OECD, 2020b).

1. Medium–high earnings (between the median and high earnings)
2. Medium–low earnings (between the median and low earnings)
3. Low earnings (less than 0.6 of the median population)
Net earnings per hour Combination of: (a) net monthly earnings from your main paid job; b) how many hours do you usually work per week in your main paid job? 0. High earnings (more than 1.5 of the median population)
1. Medium–high earnings (between the median and high earnings)
2. Medium–low earnings (between the median and low earnings)
3. Low earnings (less than 0.6 of the median population)
  1. aItem discarded after further analysis.

Appendix 2 Characteristics of complete and incomplete cases (European Working Conditions Survey 2015, selected countriesa)

  Overall   Continental   Scandinavian   Anglo-Saxon   Southern   Central-Eastern  
  C
n = 18435 		I
n = 4120 		χ 2 C
n = 7092 		I
n = 1282 		χ 2 C
n = 3170 		I
n = 214 		χ 2 C
n = 1597 		I
n = 354 		χ 2 C
n = 3105 		I
n = 1199 		χ 2 C
n = 3471 		I
n = 1071 		χ 2
Gender
 Men 8737 (47.40) 1984 (48.16) – 3445 (48.58) 632 (49.30) – 1472 (46.45) 100 (46.73) – 789 (49.44) 171 (48.31) – 1555 (50.10) 584 (48.71) – 1476 (42.52) 497 (46.41) *
 Women 9694 (52.60) 2136 (51.84) 3646 (51.42) 650 (50.70)   1697 (53.55) 114 (53.27)   807 (50.56) 183 (51.69)   1549 (49.90) 615 (51.29)   1995 (57.48) 574 (53.59)  
Age
 16–25 1543 (8.37) 358 (8.69) – 606 (8.54) 124 (9.67) – 288 (9.09) 45 (21.03) * 159 (9.96) 36 (10.17) – 229 (7.38) 71 (5.92) – 261 (7.52) 82 (7.66) –
 26–35 4152 (22.52) 847 (20.56) 1674 (23.60) 266 (20.75) 614 (19.37) 28 (13.08) 367 (22.98) 71 (20.06) 694 (22.35) 253 (21.10) 803 (23.13) 229 (21.38)
 36–45 4942 (26.81) 1146 (27.82) 1872 (26.40) 326 (25.43) 767 (24.20) 38 (17.76) 434 (27.18) 93 (26.27) 973 (1.34) 376 (31.36) 896 (25.81) 313 (29.23)
 56–55 5153 (27.95) 1183 (28.71) 1966 (27.72) 384 (29.95) 902 (18.90) 47 (26.17) 429 (26.86) 97 (27.40) 836 (26.92) 366 (30.53) 1020 (29.39) 289 (26.98)
 56–64 2645 (14.35) 586 (14.22) 974 (13.73) 182 (14.20) 599 (18.90) 56 (26.17) 208 (13.02) 57 (16.10) 373 (12.01) 133 (11.09) 491 (14.15) 158 (14.75)
Place of birth
 Country of residence 16218 (88.55) 3685 (90.16) * 5962 (84.14) 1094 (85.47) – 2883 (91.00) 191 (89.25) – 1344 (84.32) 288 (81.59) – 2838 (91.43) 1118 (93.32) * 3191 (94.86) 994 (95.39) –
 Other 2098 (11.45) 402 (9.84) 1124 (15.86) 186 (14.53) 285 (9.00) 23 (10.75) 250 (15.68) 65 (18.41) 266 (8.57) 80 (6.68) 173 (5.14) 48 (4.61)
Educational attainment
 Low 2682 (14.58) 630 (15.44) – 976 (13.79) 207 (16.30) – 252 (7.96) 32 (14.95) * 390 (24.62) 99 (28.61) – 873 (28.15) 238 (19.97) * 191 (5.51) 54 (5.10) –
 Medium 9107 (49.50) 2047 (50.17) 3830 (54.10) 658 (51.81) 1326 (41.91) 100 (46.73) 422 (26.64) 102 (29.48) 1352 (43.60) 528 (44.30) 2177 (62.76) 659 (62.29)
 High 6608 (35.92) 1403 (34.39) 2273 (32.11) 405 (31.89) 1586 (50.13) 82 (38.32) 772 (48.74) 145 (41.91) 876 (28.25) 426 (35.74) 1101 (31.74) 345 (32.61)
Mental health
 Good 15460 (83.86) 3434 (83.35) – 5920 (83.47) 1095 (85.41) – 2748 (86.69) 179 (83.64) – 1254 (78.52) 287 (81.07) – 2715 (87.44) 1015 (84.65) * 2823 (81.33) 858 (80.11) –
 Fair 2975 (16.14) 686 (16.65) 1172 (16.53) 187 (14.59) 422 (13.31) 35 (6.36) 343 (21.48) 67 (18.93) 390 (12.56) 184 (15.35) 648 (18.67) 213 (19.89)
  1. C Complete cases, I Incomplete cases. χ2 Chi-squared test
  2. *p value < 0.005
  3. aCountries included: Austria, Belgium, Croatia, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland and the UK

Appendix 3 Multilevel models of mental health, complete case analysis (European Working Conditions Survey 2015, selected countriesa)

  M0 M1 M2 M3 M4
  OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Men
 Fixed effects
  Intercept 0.14 (0.13–0.16) 0.04 (0.04–0.16) 0.04 (0.03–0.06) 0.03 (0.01–0.10) 0.03 (0.01–0.10)
  EPRES-E
   Q1 – – (ref) (ref) (ref) (ref) (ref) (ref) (ref) (ref)
   Q2 – – 1.39 (1.16–1.67) 1.39 (1.60–1.67) 1.39 (1.16–1.67) 1.41 (1.08–1.85)
   Q3 – – 1.94 (1.63–2.33) 1.94 (1.62–2.32) 1.94 (1.62–2.32) 1.77 (1.35–2.32)
   Q4 – – 3.20 (2.68–3.81) 3.16 (2.66–3.77) 3.17 (2.66–3.78) 3.03 (2.34–3.92)
  Age – – 1.01 (1.01–1.02) 1.01 (1.01–1.02) 1.01 (1.01–1.02) 1.01 (1.01–1.02)
  Place of birth
   Country of residence – – (ref) (ref) (ref) (ref) (ref) (ref) (ref) (ref)
   Other – – 0.95 (0.80–1.13) 0.95 (0.80–1.13) 0.94 (0.79–1.12) 0.95 (0.80–1.13)
  Educational attainment
   Low – – (ref) (ref) (ref) (ref) (ref) (ref) (ref) (ref)
   Medium – – 1.03 (0.86–1.21) 1.02 (0.87–1.20) 1.02 (0.87–1.20) 1.01 (0.86–1.18)
   High – – 1.10 (0.92–1.32) 1.10 (0.92–1.31) 1.10 (0.92–1.31) 1.10 (0.91–1.30)
  Welfare state
   Continental – – – – (ref) (ref) (ref) (ref) (ref) (ref)
   Scandinavian – – – – 0.79 (0.56–1.09) 0.82 (0.54–1.24) 0.68 (0.40–1.14)
   Anglo-Saxon – – – – 1.29 (0.86–1.93) 1.41 (0.85–2.34) 1.44 (0.78–2.65)
   Southern – – – – 0.76 (0.55–1.07) 0.78 (0.44–1.37) 0.98 (0.51–1.89)
   Central-Eastern – – – – 1.02 (0.75–1.38) 1.16 (0.62–2.16) 0.81 (0.37–1.77)
  EPRES-E*Welfare states
   Q2*Scandinavian – – – – – – – – 1.11 (0.66–1.87)
   Q2*Anglo-Saxon – – – – – – – – 0.94 (0.54–1.62)
   Q2*Southern – – – – – – – – 0.69 (0.40–1.20)
   Q2*Central-Eastern – – – – – – – – 1.31 (0.70–2.44)
   Q3*Scandinavian – – – – – – – – 1.39 (0.83–2.34)
   Q3*Anglo-Saxon – – – – – – – – 1.14 (0.67–1.93)
   Q3*Southern – – – – – – – – 0.82 (0.48–1.38)
   Q3*Central-Eastern – – – – – – – – 1.52 (0.85–2.73)
   Q4*Scandinavian – – – – – – – – 1.39 (0.84–2.31)
   Q4*Anglo-Saxon – – – – – – – – 0.87 (0.53–1.44)
   Q4*Southern – – – – – – – – 0.75 (0.46–1.21)
   Q4*Central-Eastern – – – – – – – – 1.54 (0.89–2.69)
 Random effects
  Intercept 0.07 (0.03–0.14) 0.07 (0.04–0.16) 0.05 (0.02–0.12) – – – –
  EPRES-E – – – – – – 0.03 (0.02–0.11) 0.04 (0.02–0.10)
  Covariance – – – – – – – – 0.04 (0.01–0.08)
Women
 Fixed effects
  Intercept 0.17 (0.15–0.19) 0.07 (0.05–0.09) 0.07 (0.05–0.10) 0.06 (0.03–0.12) 0.03 (0.01–0.09)
  EPRES-E
   Q1 – – (ref) (ref) (ref) (ref) (ref) (ref) (ref) (ref)
   Q2 – – 1.20 (1.02–1.42) 1.20 (1.04–1.41) 1.20 (1.02–1.41) 1.09 (0.84–1.47)
   Q3 – – 1.62 (1.38–1.90) 1.61 (1.51–1.89) 1.62 (1.38–1.90) 1.32 (1.03–1.68)
   Q4 – – 2.39 (2.04–2.80) 2.38 (2.51–2.79) 2.39 (2.04–2.80) 2.03 (1.61–2.56)
  Age – – 1.01 (1.01–1.02) 1.01 (1.01–1.02) 1.01 (1.01–1.02) 1.01 (1.01–1.02)
  Place of birth
   Country of residence – – (ref) (ref) (ref) (ref) (ref) (ref) (ref) (ref)
   Other – – 0.95 (0.81–1.11) 0.95 (0.78–1.11) 0.94 (0.80–1.10) 0.94 (0.81–1.10)
  Educational attainment
   Low – – (ref) (ref) (ref) (ref) (ref) (ref) (ref) (ref)
   Medium – – 0.89 (0.77–1.04) 0.89 (0.73–1.03) 0.89 (0.77–1.04) 0.88 (0.76–1.03)
   High – – 1.05 (0.90–1.23) 1.05 (0.89–1.22) 1.05 (0.90–1.23) 1.06 (0.90–1.23)
  Welfare state
   Continental – – – – (ref) (ref) (ref) (ref) (ref) (ref)
   Scandinavian – – – – 0.91 (0.53–1.31) 0.79 (0.51–1.22) 0.70 (0.42–1.17)
   Anglo-Saxon – – – – 1.17 (0.58–1.84) 1.58 (0.91–2.73) 1.32 (0.68–2.56)
   Southern – – – – 0.86 (0.49–1.24) 1.12 (0.62–1.99) 0.91 (0.46–1.78)
   Central-Eastern – – – – 1.09 (0.68–1.52) 1.94 (0.99–3.80) 1.18 (0.55–2.55)
 EPRES-E*Welfare states
   Q2*Scandinavian – – – – – – – – 1.07 (0.69–1.66)
   Q2*Anglo-Saxon – – – – – – – – 1.07 (0.60–1.91)
   Q2*Southern – – – – – – – – 1.27 (0.75–2.15)
   Q2*Central-Eastern – – – – – – – – 1.45 (0.87–2.42)
   Q3*Scandinavian – – – – – – – – 1.25 (0.81–1.91)
   Q3*Anglo-Saxon – – – – – – – – 1.18 (0.69–2.02)
   Q3*Southern – – – – – – – – 1.43 (0.87–2.33)
   Q3*Central-Eastern – – – – – – – – 1.89 (1.16–3.05)
   Q4*Scandinavian – – – – – – – – 1.10 (0.72–1.68)
   Q4*Anglo-Saxon – – – – – – – – 1.34 (0.82–2.20)
   Q4*Southern – – – – – – – – 1.15 (0.71–1.85)
   Q4*Central-Eastern – – – – – – – – 1.79 (1.13–2.84)
 Random effects
  Intercept 0.07 (0.04–0.14) 0.08 (0.04–0.16) 0.07 (0.04–0.14) – – – –
  EPRES-E – – – – – – 0.06 (0.03–0.12) 0.06 (0.03–0.12)
  Covariance – – – – – – – – 0.06 (0.01–0.10)
  1. M0: intercept-only. M1: individual-level variables. M2: M1 + country-level variable. M3: M2 + random slope for EPRES-E. M4: M3 + interaction term
  2. Significant results (p < 0.05) are in bold
  3. aCountries included: Austria, Belgium, Croatia, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland and the UK

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Padrosa, E., Vanroelen, C., Muntaner, C. et al. Precarious employment and mental health across European welfare states: a gender perspective. Int Arch Occup Environ Health (2022). https://doi.org/10.1007/s00420-022-01839-7

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Keywords

  • Precarious employment
  • Welfare states
  • Mental health
  • Gender
  • Europe
  • Multi-level