RESEARCH PAPER
Territorial variation in mortality from causes amenable to medical care in Poland
 
More details
Hide details
1
Institute of Statistics and Demography, Warsaw School of Economics, Poland
 
Ann Agric Environ Med 2017;24(3):489–495
KEYWORDS:
ABSTRACT:
Introduction and objective:
This study examines the geographical variation of amenable mortality in Poland, focusing primarily on the role of health care resources at the level of administrative districts and regions, and selected area socioeconomic characteristics as explanatory factors. The concept was used of amenable mortality, based on the assumption that deaths from certain causes should not occur in the presence of timely and effective health care.

Material and Methods:
Standardized death rates (SDR) from causes considered amenable to health care and, separately, for ischaemic heart disease (IHD), were calculated for each of 379 districts (NUTS 4 level) in Poland in 1991–1995 and 2006–2010, using unit mortality data from the National Causes of Death Register. The analytical procedure involved spatial analysis of the distribution of amenable mortality rates, selection of explanatory variables and fitting multilevel regression models using area-level and regional-level characteristics.

Results:
The results indicate that mortality from conditions which have become amenable to medical intervention has generally decreased in all districts of Poland in the past two decades. Considerable territorial variation in mortality can be observed. Since the 1990s, these differences have been reduced for IHD-related mortality and have increased for amenable mortality.

Conclusions:
The presented analysis only partly confirms the correlation between variables reflecting the infrastructure of health care resources and the territorial variation in mortality from these two categories of causes of death. Significant correlations with variation in mortality are revealed for the number of primary care physicians (at district level) and the number of specialist practitioners (at regional level). However, after controlling for socioeconomic variables, such as education and low income, the effect of the health care infrastructure-related variables was considerably reduced. The multi-level models also revealed a substantial variation at the regional level, which implies that there are other unobserved contextual influences on amenable mortality at this level.

CORRESPONDING AUTHOR:
Wiktoria Wróblewska   
Institute of Statistics and Demography, Warsaw School of Economics, Poland
 
REFERENCES (30):
1. Rutstein D, Berenberg W, Chalmers T, Child C, Fishman A, Perrin E. Measuring the quality of medicalcare. N Engl J Med 1976; 294: 582–588.
2. Gay J, Paris V, Devaux M, de Looper M. Mortalityamenable to healthcare in 31 OECD countries: estimates and methodologicalissues. Paris, OECD, 2011.
3. Nolte E, Scholz R, Shkolnikov V, McKee M. The contribution of medical care to changing life expectancy in Germany and Poland. SocSci Med 2002; 55(11): 1905–1921.
4. Velkova A, Wolleswinkel-van den Bosch JH, Mackenbach JP. The east-west life expectancy gap: Differences in mortality from conditions amenable to medical intervention. Int J Epidemiol 1997; 26: 75–84.
5. Plug I, Hoffmann R, Artnik B, Bopp M, Borrell C, Costa G, et al.. Socioeconomic inequalities in mortality from conditions amenable to medical interventions: do they reflect inequalities in access or quality of health care?. BMC Public Health 2012; 12(1): 346. doi:10.1186/1471–2458–12–346.
6. Stirbu I, Kunst AE, Bopp M, Leinsalu M, Regidor E, Esnaola S, Costa G, Martikainen P, Borrell C, Deboosere P, Kalediene R, Rychtarikova J, Artnik B, Mackenbach JP. Educational inequalities in avoidable mortality in Europe. J Epidemiol Community Health 2010; 64(10): 913–920.
7. Charlton J, Hartley R, Silver R, Holland W. Geographicalvariation in mortality from conditionsamenable to medical intervention in England and Wales. Lancet 1983; 1: 691–696.
8. Nolte E, McKee M. Measuring the health of the nations: how much isattributable to health care? Ananalysis of mortality amenable to medical care. BMJ 2003; 327: 1129–1132.
9. Nolte E, McKee M. Measuring the health of nations: updating anearlier analysis. HealthAff 2008; 27: 58–71.
10. Mackenbach J. The contribution of medical care to mortality decline: McKeownrevisited. J ClinEpidemiol 1996; 19: 1207–1213.
11. Poikolainen K, Eskola J. The effect of health services on mortality: decline in deathrates from amenable and non-amenablecauses in Finland, 1969–1981. Lancet 1986; 1: 199–202.
12. Nolte E, McKee M. Does health care savelives? Avoidable mortality revisited. London, The Nuffield Trust, 2004.
13. Carr-Hill RA, Hardman GF, Russell IT. Variations in avoidable mortality and variations in health care resources. Lancet 1987; 1: 1789–1792.
14. Mackenbach JP, Bouvier-Colle MH, Jougla E. “Avoidable” mortality and health services: A review of aggregate data studies. J Epidemiol Community Health, 1990; 44(2): 106–111.
15. Mackenbach JP, Looman CW, Kunst AE, Habbema D, van der Maas PJ. Regional differences in decline of mortality from selected conditions: The Netherlands, 1969–1984. Int J Epidemiol 1988; 17: 821–829.
16. Tobias M, Yeh L. How much does health care contribute to health gain and to health inequality? Trends in amenable mortality in New Zealand 1981–2004. Aust N Z J Public Health 2009; 33(1): 70–78.
17. Lumme S, Sund R, Leyland A, Keskimäki I. Socioeconomic equity in amenable mortality in Finland 1992–2008. SocSci Med 2012;75(5): 905–913.
18. Westerling R, Gullberg A, Rosen M. Socioeconomic differences in ‘avoidable’ mortality in Sweden, 1986–1990. Int J Epidemiol 1996; 25: 560–567.
19. Wojtyniak B, Rabczenko D, Pokarowski P, Poznańska A, Stokwiszewski J. Atlas of mortality in Poland, 2008–2010 [in Polish]. National Institute of Public Health – National Institute of Hygiene, Warsaw 2012.
20. Anselin L. Local indicators of spatial association—LISA. Geogr Anal 1995; 27: 93–115.
21. Anselin L, Griffith D. Do spatial effects really matter in regression analysis. Pap RegSciAssoc 1988; 65: 11–34.
22. Snijders T, Bosker R. Multilevel analysis. An introduction to basic and advanced multilevel modeling. 2nd ed. London, Sage, 2002.
23. Diez Roux AV. A glossary for multilevel analysis, J Epidemiol Community Health 2002; 56: 588–594.
24. Enders CK, Tofighi D. Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychol Methods 2007; 12: 121–138.
25. Macinko J, Starfield B, Shi L. Primary care systems and health outcomes in Organization for Economic Cooperation and Development (OECD) countries. Health Serv Res 2003; 38(3): 831–865.
26. Continelli T, McGinnis S, Holmes T. The effect of local primary care physician supply on the utilization of preventive health services in the United States. Health Place 2010; 16(5): 942–951.
27. French KM, Jones K. Impact of definition on the study of avoidable mortality: Geographical trends in British deaths 1981–1998 using Charlton and Holland’s definitions, SocSci Med 2006; 62(6): 1443–1456.
28. Simonato L, Ballard T, Bellini P, Winkelmann R. Avoidable mortality in Europe 1955–1994: A plea for prevention. J Epidemiol Community Health 1998; 52(10): 624–630.
29. Mackenbach JP. The persistence of health inequalities in modern welfare states: the explanation of a paradox. SocSci Med 2012; 75(4): 761–769.
30. Van Doorslaer E, Koolman X. Explaining income-related inequalities in doctor utilisation in Europe. Health Econ 2004: 13(7): 629–647.
eISSN:1898-2263
ISSN:1232-1966