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Who gets a mammogram amongst European women aged 50-69 years and why are there such large differences across European countries?

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  • Wübker, Ansgar

Abstract

On the basis of the Survey of Health, Ageing, and Retirement (SHARE), we analyse the determinants of who engages in mammography screening focusing on European women aged 50-69 years. A special emphasis is put on the measurement error of subjective life expectancy and on the measurement and impact of physician quality. Our main findings are that physician quality, better education, having a partner, younger age and better health are associated with higher rates of receipt. The impact of subjective life-expectancy on screening decision substantially increases after taking measurement error into account. In light of the enormous differences in mammography screening rates between the European countries that can be detected even if several individual characteristics are taken into account, we explore in a second step the causes of these screening differences using newly available data from the SHARELIFE. The results reveal that in countries with low screening rates (e.g. Denmark, Greece and Poland) many reasons (financial restrictions, time costs, access barriers, lack of information, not usual and low perceived benefits of screening) are significant predictors of not receiving a mammogram. In contrast in countries with high screening rates such as the Netherlands only beliefs regarding the benefits of mammograms (Not considered to be necessary) and the cause Not usual to get this type of care seem to be important screening barriers.

Suggested Citation

  • Wübker, Ansgar, 2011. "Who gets a mammogram amongst European women aged 50-69 years and why are there such large differences across European countries?," Wittener Diskussionspapiere zu alten und neuen Fragen der Wirtschaftswissenschaft 15/2011, Witten/Herdecke University, Faculty of Management and Economics.
  • Handle: RePEc:zbw:uwhdps:152011
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    References listed on IDEAS

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    1. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    2. Gabriel Picone & Frank Sloan & Donald Taylor, 2004. "Effects of Risk and Time Preference and Expected Longevity on Demand for Medical Tests," Journal of Risk and Uncertainty, Springer, vol. 28(1), pages 39-53, January.
    3. Stephen T. Parente & David S. Salkever & Joan DaVanzo, 2005. "The role of consumer knowledge of insurance benefits in the demand for preventive health care among the elderly," Health Economics, John Wiley & Sons, Ltd., vol. 14(1), pages 25-38, January.
    4. Ciro Avitabile & Tullio Jappelli & Mario Padula, 2008. "Screening Tests, Information, and the Health-Education Gradient," CSEF Working Papers 187, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy, revised 28 Apr 2008.
    5. Byrne, Margaret M. & Thompson, Peter, 2001. "Screening and preventable illness," Journal of Health Economics, Elsevier, vol. 20(6), pages 1077-1088, November.
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    More about this item

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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