How does availability of county-level healthcare services shape terminal decline in well-being?
Both lifespan psychology and life course sociology highlight that contextual factors influence individual functioning and development. In the current study, we operationalize context as county-level care services in inpatient and outpatient facilities (e.g., number of care facilities, privacy in facilities) and investigate how the care context shapes well-being in the last years of life. To do so, we combine 29 waves of individual-level longitudinal data on life satisfaction from now deceased participants in the nationwide German Socio-Economic Panel Study (N = 4557; age at death: M = 73.35, SD = 14.20; 47% women) with county-level data from the Federal Statistical Office. Results from three-level growth models revealed that having more inpatient care facilities, more employees per resident, and more staff in administration are each uniquely associated with higher late-life well-being, independent of key individual (age at death, gender, education, disability) and county (affluence, demographic composition) characteristics. Number of employees in physical care, residential comfort, and flexibility and care indicators in outpatient institutions were not found to be associated with levels or change in well-being. We take our results to provide empirical evidence that some contextual factors shape well-being in the last years of life and discuss possible routes how local care services might alleviate terminal decline.
KeywordsCounty Socio-Economic Panel Life satisfaction Care Regional differences
- Bronfenbrenner U (1979) The ecology of human development: experiments by nature and design. Harvard University Press, CambridgeGoogle Scholar
- Federal Statistical Office (2012) Care statistics. Care in the framework of care insurance. County comparison 2009 [Pflegestatistik. Pflege im Rahmen der Pflegeversicherung. Kreisvergleich 2009]. WiesbadenGoogle Scholar
- Federal Statistical Office (2014) Care statistics 2013. Care in the framework of care insurance. Results in Germany [Pflegestatistik 2013. Pflege im Rahmen der Pflegeversicherung. Deutschlandergebnisse]. WiesbadenGoogle Scholar
- Gerstorf D, Ram N (2012) Late-life: a venue for studying the mechanisms by which contextual factors influence individual development. In: Whitbourne SK, Sliwinski MJ (eds) Handbook of adulthood and aging. Wiley, New York, pp 49–71Google Scholar
- Lawton MP (1982) Competence, environmental press, and the adaptation of older people. In: Lawton MP, Windley PG, Byerts TO (eds) Aging and the environment. Springer, New York, pp 33–59Google Scholar
- Little RJA, Rubin DB (1987) Statistical analysis with missing data. Wiley, New YorkGoogle Scholar
- OECD (2011) Premature mortality. In: Health at a glance 2011: OECD indicators. OECD Publishing, Paris. doi:10.1787/health_glance-2011-5-en
- Ram N, Grimm K (2015) Growth curve modeling and longitudinal factor analysis. In: Overton W, Molenaar PCM (eds) Handbook of child psychology: vol 1. Theoretical models of human development, 7th edn. Wiley, HobokenGoogle Scholar
- SAS Institute Inc (2009) SAS/STAT user’s guide 9.2. SAS Institute Inc, CaryGoogle Scholar
- World Health Organization (2002) Towards a common language for functioning, disability and health: ICF—the International classification of functioning, disability and health. World Health Organization, GenevaGoogle Scholar