Psychiatric consequences of a father’s leave policy by nativity: a quasi-experimental study in Sweden

Abstract

BackgroundParental leave use has been found to promote maternal and child health, with limited evidence of mental health impacts on fathers. How these effects vary for minority populations with poorer mental health and lower leave uptake, such as migrants, remains under-investigated. This study assessed the effects of a Swedish policy to encourage fathers’ leave, the 1995 Father’s quota, on Swedish-born and migrant fathers’ psychiatric hospitalisations.MethodsWe conducted an interrupted time series analysis using Swedish total population register data for first-time fathers of children born before (1992–1994) and after (1995–1997) the reform (n=198 589). Swedish-born and migrant fathers’ 3-year psychiatric hospitalisation rates were modelled using segmented negative binomial regression, adjusting for seasonality and autocorrelation, with stratified analyses by region of origin, duration of residence, and partners’ nativity.ResultsFrom immediately pre-reform to post-reform, the proportion of fathers using parental leave increased from 63.6% to 86.4% of native-born and 37.1% to 51.2% of migrants. Swedish-born fathers exhibited no changes in psychiatric hospitalisation rates post-reform, whereas migrants showed 36% decreased rates (incidence rate ratio (IRR) 0.64, 95% CI 0.47 to 0.86). Migrants from regions not predominantly consisting of Organisation for Economic Cooperation and Development countries (IRR 0.50, 95% CI 0.19 to 1.33), and those with migrant partners (IRR 0.23, 95% CI 0.14 to 0.38), experienced the greatest decreases in psychiatric hospitalisation rates.ConclusionThe findings of this study suggest that policies oriented towards promoting father’s use of parental leave may help to reduce native–migrant health inequalities, with broader benefits for family well-being and child development.

Context and health: a systematic review of natural experiments among migrant populations

“…Another strong natural experiment looking at the composition of school classes shows a positive effect of increased proportions of foreign-born co-students on migrant mental health and health-risk behaviour, although this effect does not last into adulthood 49 . Studies assessing the effect of policy contexts on adult and child mental health find moderate but consistent evidence of the positive impacts of inclusionary migration, health and social policies 37,38,47,50,57 . The evidence on the mental health impacts of restrictive policies such as strengthened migration enforcement 53 , repatriation 64 or reduced unemployment benefits 26 is mixed.…”

“…With respect to the source of variation in exposure underlying the natural experiments (see Panel 2), 17 studies make use of residential dispersal 27,29–31,34,36,40–43,46,61,67–71 , 10 use regional variation in a policy implementation or natural event 32,33,47–49,52,54,58,60,63 , seven studies make use of the timing of a policy or event 26,37,39,53,55,56,64 and two studies use the place of birth 35,62 (Table1). Nine studies combine two or more of these mechanisms in order to further strengthen the natural experiment design.…”

“…We found four types of contextual effects which were examined across studies: contextual factors of the place of residence in receiving countries (n=15) 27,29–32,34,36,40–43,46,49,60,61 , migration-context interactions (n=10) 59,62,63,65–71 , policy contexts (n=20) 26,28,33,37–39,44,45,47,48,50–58,64 , as well as cultural factors as context (n=1) 35 , the latter being an outlier in this set. Studies related to “contextual factors of the place of residence” examined specific regional characteristics such as regional deprivation, income inequality, neighbourhood disadvantage or migrant density among migrants in the resettlement phase.…”

“…Just under half of studies (n=22) 28,30–36,38,40–44,46,49,53,55,63–66 use regression adjustment as their statistical analysis approach (Appendix Table S6). Other popular approaches include difference-in-difference analyses (n=10) 39,47,48,51,52,54,56–59 , instrumental variables (n=8) 27,60,62,67–71 and regression discontinuity (n=3) 26,37,50 . 17 studies 27,28,30,31,33,37–39,45,47,48,50–52,54,57,62 use the natural experiment as “intention to treat”, e.g.…”

“…Other popular approaches include difference-in-difference analyses (n=10) 39,47,48,51,52,54,56–59 , instrumental variables (n=8) 27,60,62,67–71 and regression discontinuity (n=3) 26,37,50 . 17 studies 27,28,30,31,33,37–39,45,47,48,50–52,54,57,62 use the natural experiment as “intention to treat”, e.g. by program eligibility, rather than measuring actual treatment assignment.…”