Excess Mortality Risks in Institutions: The Influence of Health and Disability Status
- 546 Downloads
Mortality in the institutionalized aged population is generally recognized as being considerably higher than among those living independently; whereas among those living independently, there is a greater risk of mortality among those living alone than among those living with other adults (generally with spouse and/or children). However, given that the institutionalized population is liable to be poorer, and in poorer health than the independent-living population, it is unclear whether the higher mortality risk among the institutionalized population results from their poorer health, or from other causes associated with institutionalization. The Belgian Census of 2001, coupled with a near-complete follow-up of deaths over the subsequent year (2002), enables us to compute a reasonable measure of health at the time of the census and thus separate out the effects of health status and living conditions on mortality. Taken across the entire population of Belgian nationals resident in Belgium and aged 65 and above at the time of the census (N = 1.64 million cases with full data), and controlling for background characteristics, we find that except at very old ages, those living in old age homes have a higher risk of mortality than those living in private housing, irrespective of health status. We conclude that while much of the apparently higher mortality of the institutionalized aged population may be attributable to the generally poorer health of those living in institutions, there is nonetheless a salutogenic effect of living independently in private housing, whatever the individual’s health status.
KeywordsBelgium Old age Ill-health Institutionalisation Gender differences
- Adler, D. (2005). Vioplot: Violin plot. R package version 0.2. http://wsopuppenkiste.wiso.uni-goettingen.de/~dadler. Accessed 9 Feb 2011.
- Börsch-Supan, A., Mcfadden, D., & Schnabel, R. (1996). Living arrangements, health and wealth effects. In D. Wise (Ed.), Advances in the economics of aging (pp. 193–218). Chicago: University of Chicago Press.Google Scholar
- Breiman, L., Friedman, J. H., Olschen, C. J., & Stone, R. A. (1984). Classification and regression trees. Monterey: Wadsworth.Google Scholar
- Breuer, B., Wallenstein, S., Feinberg, C., Camargo, M.-J. F., & Libow, L. S. (1998). Assessing life expectancies of older nursing home residents. Journal of the American Geriatrics Society, 46(8), 954–962.Google Scholar
- Hintze, J. L., & Nelson, R. D. (1998). Violin plots: A box plot-density trace synergism. The American Statistician, 52(2), 181–184.Google Scholar
- Hjaltadattir, I., Halberg, I. R., Ekwall, A. K., & Nyberg, P. (2011). Predicting mortality of residents at admission to nursing home: A longitudinal cohort study. BMC Health Services Research, 11 (Article number 86, pages 1–11.).Google Scholar
- Murphy, M. (1995). Assessing the link between household and family living arrangements and health. In G. Wunsch & A. Hancioglu (Eds.), Morbidity and mortality data: Problems of comparability. Proceedings of the European Association for Population Studies and the Hacettepe Institute of Population Studies Workshop, Ürgüp, Turkey, 18–20 October 1995.Google Scholar
- Nenadic, O. & Greenacre, M. (2007) Correspondence Analysis in R, with two- and three-dimensional graphics: The ca package. Journal of Statistical Software 20(3):1–13.Google Scholar
- Therneau, T. M., & Atkinson, B. (2011). Rpart: Recursive Partitioning. R package version 3.1–49. R port by Brian Ripley. http://CRAN.R-project.org/package=rpart. Accessed 8 May 2011.
- Tukey, J. W. (1997). Exploratory data analysis. Reading: Addison.Google Scholar