Social Determinants of Mental Health and Mental Health Service Use in the German National Cohort (NAKO)

(Please check the files folder for a nicely formatted version of this preregistration.) Social determinants contribute at least 50% to health outcomes and health inequities (World Health Organization, 2025). Social determinants are “…broadly defined as the conditions in which people are born, grow, live, work and age, and people’s access to power, money and resources” (World Health Organization, 2026) and they shape health outcomes even more than access to healthcare or genetic predispositions (World Health Organization, 2025). Generally, social determinants can shape health outcomes positively or negatively depending on the expression of the determinant, meaning that e.g. income security may predict better mental health, whereas income insecurity may lead to a deterioration of mental health (American Psychiatric Association, 2022; Kirkbride et al., 2024). In this preregistration, we will refer to these detrimental expressions of social determinants as social risk factors. The association of these social risk factors with mental health outcomes, especially depression and anxiety as the most prevalent mental health problems (Jacobi et al., 2014; Robert Koch-Institut, Abteilung für Epidemiologie und Gesundheitsmonitoring, 2024), is evident across various domains. Among these, living arrangements such as being single and living alone, in rented or family-owned housing, has been found to be associated with higher risk of experiencing mental health disorders (Morgan et al., 2008). In addition, being unemployed, having lower education, and lower socio-economic status (SES) has been shown to be associated with a higher risk of experiencing mental health problems (Kirkbride et al., 2024). Furthermore, having parents with a low SES, being exposed to childhood trauma, and being socially isolated as an adult are associated with an increased risk of experiencing mental health problems (Kirkbride et al., 2024; Morgan et al., 2008). Last, migrants as well as members of ethnic minority groups report lower mental health than their non-migrant, ethnic majority counterparts (Kessler et al., 1999; Kirkbride et al., 2024; Vonneilich et al., 2023). These social risk factors can interact with each other and combine in various ways and, thereby, increase risk of adverse mental health outcomes. First, a primary social risk factor can influence the likelihood of exposure to a more proximal risk factor, which in turn may increase the risk of experiencing a mental health problem (mediation). Second, social risk factors can combine synergistically, meaning that their combined effect is bigger than their sum. Finally, mediation and synergy can also occur in parallel (mediated synergy; Susser et al., 2006). In addition to associations between social risk factors and mental health, several studies have shown similar links between social risk factors and mental healthcare use. Balshi et al. (2025) for example found that for those suffering from depression/anxiety, being female, non-Hispanic White, employed, and non-heterosexual influenced the likelihood of not receiving antidepressant or anxiolytic medication. Furthermore, being a first-generation migrant as well as having a lower socio-economic status has been found to decrease the likelihood of using mental healthcare (Henking et al., 2023a; Wiessner et al., 2024). Beyond these social risk factors, the presence of comorbid mental health problems in comparison to only one mental health problem has been shown to increase to odds of using mental healthcare (Mack et al., 2014). Examining how these observable social determinants typically cluster across a population allows inference about unobserved (latent) classes, such as socio-demographic or clinical profiles of groups of individuals who, despite suffering from mental health problems, are not receiving mental healthcare (Ballard et al., 2015; Wiessner et al., 2024). One way of grouping individuals into latent classes based on observable variables is latent class analysis (LCA; Hadzi-Pavlovic, 2009). Despite evidence on the association of social risk factors with mental health outcomes and mental healthcare use, a large-scale study that examines not only how individual social determinants are directly associated with mental health outcomes and mental healthcare use, but also how they interact and combine, is currently lacking for the German population. Aims The proposed study will therefore use data from Germany’s largest prospective cohort study to examine in part 1, how social determinants, specifically migration status, ethnic group status, relationship status, household size, housing situation, employment status, SES, social network index, education, parental SES, and childhood trauma, interact and combine in various ways and influence risk of experiencing mental health problems, specifically depression, generalized anxiety, and psychological distress using regression analyses; and in part 2, examine how these social determinants cluster within individuals in order to identify groups of individuals with specific socio-demographic profiles who are not using mental healthcare (sufficiently) despite suffering from mental health problems using latent class analysis, in order to allow future public mental health interventions to specifically target these subpopulations. For part 1, we specifically aim to: (1) examine, whether cumulative social risk factors gradually increase the risk of suffering from mental health problems, in a dose-response fashion and (2) explore various social developmental trajectories of mental health problems via mediation, synergy, and mediated synergy. For part 2, we specifically aim to: (1) examine, whether different classes of individuals with mental health problems can be identified based on shared social determinants and (2) whether these classes can be used to predict mental healthcare use.