Evidence map›Paper›PMID 23744174›Full record

ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2014

Explaining variations in breast cancer screening across European countries.

Ansgar Wübker

Abstract read
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Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  7. Article
  8. Age-Specific Breast Density Changes in Taiwanese Women: A Cross-Sectional Study.International journal of environmental research and public health · 2020
    Article
  9. The effects of organized screening programs on the demand for mammography in Switzerland.The European journal of health economics : HEPAC : health economics in prevention and care · 2017
    Article
  10. Article
  11. Differing types of medical prevention appeal to different individuals.The European journal of health economics : HEPAC : health economics in prevention and care · 2016
    Article
  12. Article
  13. Income-related inequalities and inequities in health care services utilisation in 18 selected OECD countries.The European journal of health economics : HEPAC : health economics in prevention and care · 2015
    Article
  14. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Ansgar WübkerDepartment of Economics, Institutional Economics and Health Systems Management, Witten/Herdecke University, Alfred-Herrhausen-Str. 50, 58448, Witten, Germany, ansgar.wuebker@uni-wh.de.

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
Understanding and Improving Healthcare Decision-Making and Outcomes for People Living with Alzheimer's Disease and Related DementiasP01AG005842 · NIA · NATIONAL BUREAU OF ECONOMIC RESEARCH · PI JOSEPH J DOYLE · 1986 to 2026
$56.5M
WEALTH DISPARITIES AMONG MATURE AND OLDER ADULTSP01AG008291 · NIA · RAND CORPORATION · PI HURD, MICHAEL D · 1989 to 2018
$19.4M
RAND CENTER FOR THE STUDY OF AGINGP30AG012815 · NIA · RAND CORPORATION · PI HURD, MICHAEL D · 1999 to 2020
$13.7M
NIA NIH HHS P01 AG005842NIA NIH HHS P01 AG08291NIA NIH HHS P30 AG12815NIA NIH HHS U01 AG09740-13S2NIA NIH HHS Y1-AG-4553-01
6 · The paper itself

Abstract

objectiveIn this study I aim to explore the statistical causes of country differences in mammography screening among women aged 50-69 years in 13 European countries. I focus on the relative importance of individual (e.g. age, education, etc.) and institutional (e.g. public screening programmes) factors in explaining these differences. DATA AND

methodsI use individual level data from the first three waves (2004-2006-2009) of the SHARE as well as regional and country level data on institutional factors. The analytical approach is based on multilevel statistical models, which allow me to analyse the contribution of individual and institutional factors in explaining the variation in breast cancer screening across European countries.

resultsI find that the standard deviation in screening rates across countries increases slightly from 19.5 to 20.8 per cent after controlling for individual factors. Observed individual factors such as age, education, health status, etc., do not significantly contribute to the explanation of cross-country differences. In contrast, after controlling for observed institutional factors such as the availability of an organised screening programme, the standard deviation drops from 20.86 to 12.92 per cent. These factors can statistically explain about 40 per cent of the between-country differences in screening rates. Moreover, I found that these institutional factors seem to prevent a woman from considering a mammogram "not necessary".

conclusionThis analysis provides important insights about patient's attitudes and understanding of benefits of breast cancer prevention and highlights the importance of the availability of an organised screening programme for screening differences across European countries.

Indexed as

InternationalityAgedAge FactorsBreast NeoplasmsEarly Detection of CancerEuropeFemaleHealth BehaviorHealth Services Needs and DemandHealth StatusHumansMammographyMiddle AgedPatient Acceptance of Health CareSocioeconomic Factors

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.