Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G).

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.

Primary care in Germany: access and utilisation-a cross-sectional study with data from the German Socio-Economic Panel (SOEP).

OBJECTIVES: (1) To describe the accessibility of general practitioners (GPs) by the German population; (2) to determine factors on individual and area level, such as settlement structure and area deprivation, which are associated with the walking distance to a GP; and (3) to identify factors that may cause differences in the utilisation of any doctors. DESIGN: Cross-sectional study using individual survey data from the representative German Socio-Economic Panel (SOEP) linked with area deprivation data from the German Index of Multiple Deprivation for 2010 (GIMD 2010) and official data for settlement structure (urban/rural areas) at district level. Logistic regression models were estimated to determine the relationship of individual and area factors with the distance to a GP. Negative binomial regressions were used to analyse the association with utilisation. SETTING: Germany. POPULATION: n=20 601 respondents from the SOEP survey data 2009. PRIMARY OUTCOME MEASURE: Walking distance to a GP. SECONDARY OUTCOME MEASURE: Doctor visits. RESULTS: Nearly 70% of the sample lives within a 20 min walk to a GP. People living in the most deprived areas have a 1.4-fold (95% CI 1.3 to 1.6) increased probability of a greater walking distance compared with the least deprived quintile, even after controlling for settlement structure and individual factors. In rural districts, people have a 3.1-fold (95% CI 2.8 to 3.4) higher probability of a greater walking distance compared with those in cities. Both area deprivation and rurality have a negative relationship with the utilisation of physicians, whereas the distance to a GP is not associated with the utilisation of physicians. CONCLUSION: Walking distance to a GP depends on individual and area factors. In Germany, area deprivation is negatively correlated with the accessibility of GPs while controlling for settlement structure and individual factors. Both area factors are negatively associated with the utilisation of doctors. This knowledge could be used for future GP requirement plans.

Where people live and die makes a difference: Individual and geographic disparities in well-being progression at the end of life.

Life-span psychological research has long been interested in the contextual embeddedness of individual development. To examine whether and how regional variables relate to between-person disparities in the progression of late-life well-being, we applied three-level growth curve models to 24-year longitudinal data from deceased participants of the German Socio-Economic Panel Study (N = 3,427; age at death = 18 to 101 years). Results indicated steep declines in well-being with impending death, with some 8% of the between-person differences in both level and decline of well-being reflecting between-county differences. Exploratory analyses revealed that individuals living and dying in less affluent counties reported lower late-life well-being, controlling for key individual predictors, including age at death, gender, education, and household income. The regional variables examined did not directly relate to well-being change but were found to moderate (e.g., amplify) the disparities in change attributed to individual variables. Our results suggest that resource-poor counties provide relatively less fertile grounds for successful aging until the end of life and may serve to exacerbate disparities. We conclude that examinations of how individual and residential characteristics interact can further our understanding of individual psychological outcomes and suggest routes for future inquiry.