Long-term care use and socio-economic status in Belgium: a survival analysis using health care insurance data

van den Bosch, Karel and Geerts, Joanna and Willemé, Peter (2013): Long-term care use and socio-economic status in Belgium: a survival analysis using health care insurance data. Published in: Archives of Public Health , Vol. 71, No. 1 (January 2013): pp. 1-9.

Abstract

Background: The small but growing literature on socio-economic inequality in morbidity among older persons suggests that social inequalities in health persist into old age. A largely separate body of literature looks at the predictors of long-term care use, in particular of institutional care. Various measures of socio-economic status are often included as control variables in these studies. Review articles generally conclude that the evidence for such variables being a predictor for institutionalization is “inconclusive”. In this paper we look at the association among older persons in Belgium between one particular measure of socio-economic status – preferential status in public health care insurance – and first use of home long-term care and residential care. Preferential status entitles persons to higher reimbursement rates for health care from the public health care insurance system and is conditional on low income. We also study whether preferential status is related to the onset of five important chronic conditions and the time of death.

Methods: We use survival analysis; the source of the data is a large administrative panel of a sample representative for all older persons in Belgium (1,268,740 quarterly observations for 69,562 individuals).

Results: We find a strong association between preferential status and the likelihood of home care use, but for residential care it is small for men and non-existent for women. We also find that preferential status is significantly related to the chance of getting two out five chronic conditions – COPD and diabetes, but not dementia, hip fracture and Parkinson’s disease – and to the probability of dying (not for women). For home care use and death, the association with preferential status declines with increasing age from age 65 onwards, such that it is near zero for those aged around 90 and older.

Conclusion: We find clear associations between an indicator of low income and home care use, some chronic conditions and death. The associations are stronger among men than among women. We also find that the association declines with age for home care use and death, which might be explained by selective survival.

• Item Type: MPRA Paper
• Language: English
• Keywords: Long-term care, Socio-economic status, Morbidity, Mortality, Preferential status
• Subjects: I - Health, Education, and Welfare > I1 - Health

References

1. Van Oyen H, Charafeddine R, Deboosere P, Cox B, Lorant V, Nusselder W, Demarest S: Contribution of mortality and disability to the secular trend in health inequality at the turn of century in Belgium. Eur J Public Health 2011, 21:781–787.

2. Connolly S, O’Reilly D, Rosato M: House value as an indicator of cumulative wealth is strongly related to morbidity and mortality risk in older people: a census-based cross-sectional and longitudinal study. Int J Epidemiol 2010, 39:383–391.

3. Avendano M, Jürges H, Mackenbach JP: Educational level and changes in health across Europe: longitudinal results from SHARE. J Eur Soc Pol 2009,19:301–316.

4. Hoeck S, François G, Geerts J, Van der Hyeden J, Vandewoude M, Van Hal G: Health-care and home-care utilization among frail elderly persons in Belgium. Eur J Public Health 2012, 22:671–677.

5. Szanton SL, Seplaki CL, Thorpe RJ Jr, Allen JK, Fried LP: Socioeconomic status is associated with frailty: the Women’s Health and Aging Studies. J Epidemiol Community Health 2010, 64:63–67.

6. Grundy E, Holt G: The socioeconomic status of older adults: how should we measure it in studies of health inequalities? J Epidemiol Community Health 2001, 55:895–904.

7. Gaugler JE, Duval S, Anderson KA, Kane RL: Predicting nursing home admission in the U.S: a meta-analysis. BMC Geriatr 2007, 7:13.

8. Luppa M, Luck T, Weyerer S, König H-H, Brähler E, Riedel-Heller SG: Prediction of institutionalization in the elderly. A systematic review. Age Ageing 2010, 39:31–38.

9. Muramatsu N, Yin H, Campbell RT, Hoyem RL, Jacob MA, Ross CO: Risk of nursing home admission among older americans: does states’ spending on home- and community-based services matter? J Gerontol B Psychol Sci Soc Sci 2007, 62:S169–S178.

10. Nihtilä E, Martikainen P: Household income and other socio-economic determinants of long-term institutional care among older adults in Finland. Popul Stud (Camb) 2007, 61:299–314.

11. Sarma S, Simpson W: A panel multinomial logit analysis of elderly living arrangements: Evidence from aging in Manitoba longitudinal data. Canada. Soc Sci Med 2007, 65:2539–2552.

12. Kasper JD, Pezzin LE, Rice JB: Stability and changes in living arrangements: relationship to nursing home admission and timing of placement. J Gerontol B Psychol Sci Soc Sci 2010, 65:783–791.

13. Noël-Miller C: Spousal loss, children, and the risk of nursing home admission. J Gerontol B Psychol Sci Soc Sci 2010, 65B:370–380.

14. Cai Q, Salmon JW, Rodgers ME: Factors associated with long-stay nursing home admissions among the U.S. elderly population: comparison of logistic regression and the Cox proportional hazards model with policy implications for social work. Soc Work Health Care 2009, 48:154–168.

15. Harris Y, Cooper JK: Depressive symptoms in older people predict nursing home admission. J Am Geriatr Soc 2006, 54:593–597.

16. Kendig H, Browning C, Pedlow R, Wells Y, Thomas S: Health, social and lifestyle factors in entry to residential aged care: an Australian longitudinal analysis. Age Ageing 2010, 39:342–349.

17. Norton E: Long-Term Care, Handbook of Health Economics. 1Bth edition. Amsterdam: Elsevier; 2000:956–994.

18. Permanent sample (EPS) [L’Echantillon permanent (EPS)]. http://www.nic-ima.be/fr/imaweb/DT/content/imaweb/datas/eps/eps_introduction.html.

19. Singer JD, Willett JB: Applied longitudinal data analysis: modeling change and Event occurrence. USA: Oxford University Press; 2003.

20. Allison PD: Survival analysis using SAS: A practical guide. Cary, NC: Sas Institute Inc; 1995.

21. Van Oyen H, Deboosere P, Lorant V, Charafeddine R: Social inequalities in health in belgium [Les inégalités sociales de santé en Belgique. Gent: Academia press; http://www.belspo.be/belspo/ta/publ/academia-inegalites. soc.sante.U1579.pdf.

22. Rueda S, Artazcoz L, Navarro V: Health inequalities among the elderly in western Europe. J Epidemiol Community Health 2008, 62:492–498.

23. Ai C, Norton EC: Interaction terms in logit and probit models. Econ Lett2003, 80:123–129.

24. CM: nursing prices [tarieven verpleegkundigen] 2010. http://www.cm.be/nl/100/ziekteverzekering/erelonen_en_terugbetalingstarieven/verpleegkundige/ tarieven.jsp.

25. Geerts J, Willemé P, Mot E: Long-term care use and supply in Europe: projections for Germany, The Netherlands, Spain and Poland. Brussels: ENEPRI 2012.http://www.ancien-longtermcare.eu/sites/default/files/RR%20No% 20116%20_ANCIEN%20WP6_%20Projecting%20LTC%20Use%20&% 20Supply_UPDATED_Nov2012_OK.pdf.

26. Increased reimbursements - income thresholds [intervention majorée - plafonds des revenus]. http://www.riziv.be/citizen/fr/medical-cost/SANTH_4_4_1.htm.