Browsing by study line "Yhteiskuntatilastotiede"

This thesis examines components of an emerging topic: the interplay between immigration background and partnering in the modern Finnish context. It poses the question: how do various computational methods capture the ways that immigrant background status alters (1) the time to first union formation and (2) subsequent first union dissolutions in Finland from 1987-2020? Using longitudinal Finnish register data, the study focuses on all women residents in Finland observed from age 18 onwards during the specified period, categorized by their intergenerational immigration status. The study examines the relationship between immigration status and the two events of interest using the nonparametric Kaplan-Meier survivor function, semiparametric Cox Proportional Hazards model, and parametric survival model fitted with generalized gamma distribution. The strengths, limitations, and findings from each analytic method are compared. The results suggest three main findings: firstly, there is a clear gradient in the risk of first union formation and dissolution across women with different immigrant backgrounds in Finland, with Native Finnish women experiencing the highest risk, followed by 2.5 generation women (women with one Native Finnish parent and one 1st generation immigrant parent), 1st generation immigrant women, and finally 2nd generation women (women with two 1st generation immigrant parents). Secondly, factors including educational attainment, region of origin, rural/urban residence, and partnership homogamy based on region of origin contribute to differences in the risks for both union formation and union dissolution. Finally, despite the unique assumptions and constraints of each method, results remain consistent across all models, indicating that a variety of computational methods can provide robust insights into the complex interplay between immigration and first union dynamics in Finland. In light of the growing immigrant population and the potential influence of their first union dynamics on population change, these findings suggest alignment with segmented assimilation theory, highlighting a non-linear assimilation process influenced by socio-economic status and socio-cultural resources. The observed differences between the 2.5 and 2nd generations raise intriguing questions about the experiences of immigrant children in Finland. The 2nd generation's particularly low risk of first union formation indicates potentially unique acculturation stressors that warrant further investigation.

Mental disorders are common during childhood and they are associated with various negative consequences later in life, such as lower educational attainment and unemployment. In addition, the reduction of socioeconomic health disparities has attracted both political, research and media interest. While mental health inequalities have been found consistently in literature and regional disparities in health have been well documented in Finland altogether, the question of possible variation in mental disorder inequalities during childhood among Finnish regions is not fully examined. This master’s thesis contributes to this gap in the research with a statistical perspective and use of a multilevel logistic model, which allows random variation between levels. Using register-based data, I ask whether the association between socioeconomic status and mental disorder in childhood varies between the child’s municipality of residence, and which regional factors possibly explain the differences. The second objective of this thesis is to find out whether the use of a multilevel logistic model provides additional value to this context. The method used in the thesis is a multilevel logistic model, which can also be called a generalized linear mixed-effects model. In multilevel models, the observations are nested within hierarchical levels, which all have corresponding variables. Both intercept and slopes of independent variables can be allowed to vary between the Level 2 units. Intraclass correlation coefficient and median odds ratio (MOR) are used to measure group level variation. In addition, centering of variables and choosing a suitable analysis strategy are central steps in model application. High-quality Finnish register data from Statistics Finland and the Finnish Institute of Health and Welfare is utilised. The study sample consists of 815 616 individuals aged 4–17 living in Finland in the year 2018. The individuals who are used as Level 1 units are nested within 306 Level 2 units based on their municipality of residence. The dependent variable is a dichotomous variable indicating a mental disorder and it is based on visits and psychiatric diagnoses given in specialised healthcare during 2018. Independent variables in Level 1 are maternal education level and household income quintile, and models are controlled for age group, gender, family structure and parental mental disorders. In Level 2, the independent variables are urbanisation, major region, share of higher-educated population and share of at-risk-of-poverty children. In the final model, children with the lowest maternal education level are more likely (OR=1.37, SE=0.0026) to have mental disorders than children with the highest maternal education level. Odds ratios for the household income quintile mostly decline close to one when control variables are included. Interestingly, children from the poorest quintile have slightly lower odds for mental disorder (OR=0.84, SE=0.017) compared with children from the richest quintile. Urbanisation, share of higher-educated population and share of at-risk-of-poverty children are statistically insignificant variables. Differences are found between major regions; children from Åland are more likely (OR=1.5, SE=0.209) to have a mental disorder compared with Helsinki-Uusimaa residents, whereas children from Western Finland (OR=0.71, SE 0.053) have lower odds compared to the same reference. Random slopes for maternal education are not significant, and the model fit does not improve. However, there is some variation among municipalities (MOR=1.34), and this finding defends the usefulness of the multilevel model in the context of mental disorders in childhood. The results show that mental disorder inequalities persist in childhood, but there is complexity. Although no variation in socioeconomic inequalities among municipalities is found, there are still contextual effects between municipalities. Health policies should focus on reducing overall mental health inequalities in the young population, but it is an encouraging finding that disparities in childhood mental disorders are not shown to be stronger in some municipalities than others. Multilevel models can contribute to the methodology of future mental disorder research, if societal context is assumed to affect the outcomes of individuals.