Download PDF
Methods Inf Med 2014; 53(05): 371-379
DOI: 10.3414/ME13-01-0088
Original Articles
Schattauer GmbH

Combining Cross-sectional Data on Prevalence with Risk Estimates from a Prediction Model

A Novel Method for Estimating the Attributable Risk
B. Engelhardt
1   Department of Medical Biostatistics, Informatics and Epidemiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
8   Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for IT, Algorithmic Bioinformatics, Bonn, Germany
,
J. König
1   Department of Medical Biostatistics, Informatics and Epidemiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
,
M. Blettner
1   Department of Medical Biostatistics, Informatics and Epidemiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
,
P. Wild
2   Department of Medicine II, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
3   Center for Thrombosis and Hemostasis, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
,
T. Münzel
2   Department of Medicine II, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
,
K. Lackner
4   Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center of the Johannes Gutenberg- University Mainz, Mainz, Germany
,
S. Blankenberg
2   Department of Medicine II, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
5   University Heart Center Hamburg, Department of General and Interventional Cardiology, Hamburg, Germany
,
N. Pfeiffer
6   Department of Ophthalmology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
,
M. Beutel
7   Department of Psychosomatic Medicine and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
,
I. Zwiener
1   Department of Medical Biostatistics, Informatics and Epidemiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
› Author Affiliations
Further Information

Publication History

received:08 August 2013

accepted:10 April 2014

Publication Date:
20 January 2018 (online)

    Permissions and Reprints

Summary

Objectives: Estimation of the attributable risk for fatal diseases by combining two different data sources.

Methods: We derive a method to estimate the attributable risks of different risk factors by combining general mortality risks with upto-date prevalences of the risk factors using estimates from a risk prediction model and cross-sectional data of a cohort study. Partial attributable risks have been used to illustrate the proportions of the different risk factors for the attributable risk. In addition we derive standard errors for the attributable risk based on the Taylor series expansion. Since the data of our cohort study was sampled with the same size in each 10 years age stratum which does not reflect the age-structure of the general population, the attributable risk and its standard errors are calculated using an approach that allows the weighting of the data according to population proportions of age. The formula for the standard errors has been evaluated using bootstrap-techniques.

Results: We successfully implemented the method for the estimation of the attributable risk and its standard errors by integrating risk information using data of the HeartScore Germany and cross-sectional data emerging from the Gutenberg Health Study. The attributable risk can now be calculated without using the information of the overall disease rate. The bootstrap method shows, that the formula for the standard errors is useful.

Conclusion: Our method allows for the combination of different data sources in order to estimate attributable risks and our formula for the standard errors seems to yield a good approximation. But the validity of our method highly depends on the validity of the underlying data sources.

Keywords

Attributable risk - partial attributable risk - exposure - prevention - standard errors - cardiovascular diseases
 

  • References

  • 1 Gaber E. Gesundheitsberichterstattung des Bundes. 52nd ed. Robert-Koch-Institut. Berlin: Statistisches Bundesamt; 2011
    Search in Google Scholar
  • 2 Stamler J, Neaton JD, Garside DB, Daviglus ML. Current status: six established major risk factors - and low risk. In Marmot M, Elliott P. editors Coronary Heart Disease Epidemiology: From aetiology to public health 2nd ed.. New York: Oxford University Press Inc.; 2005: 32-70.
    Search in Google Scholar
  • 3 The International Consortium for Blood Pressure Genome-Wide Association Studies Genetic Variants in Novel Pathways Influence Blood Pressure and Cardiovascular Disease Risk. Nature 2011; 478: 103-109.
    PubMedSearch in Google Scholar
  • 4 Schulte H, Assmann G, Cullen P. Simple Scoring Scheme for Calculating the Risk of Acute Coronary Events Based on the 10-Year Follow-Up of the Prospective Cardiovascular Münster (PROCAM) Study. Circulation 2002; 105 (03) 310-315.
    CrossrefPubMedSearch in Google Scholar
  • 5 Keil U, Fitzgerald AP, Gohlke H, Wellmann J, Hense HW. Risikoabschätzung tödlicher Herz-Kreislauf-Erkrankungen. Deutsches Ärzteblatt 2005; 102 (25) A1808-12.
    PubMedSearch in Google Scholar
  • 6 Wilson PWF, D´Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of Coronary Heart Disease Using Risk Factor Categories. Circulation 1998; 97: 1837-1847.
    CrossrefPubMedSearch in Google Scholar
  • 7 Chang M, Hahn RA, Teutsch SM, Hutwagner LC. Multiple risk factors and population attributable risk for ischemic heart disease mortality in the United States 1971-1992. Journal of Clinical Epidemiology 2001; 54 (06) 634-644.
    CrossrefPubMedSearch in Google Scholar
  • 8 Reissigová J, Zvárová J. The Framingham risk function underestimated absolute coronary heart disease risk in Czech men. Methods Inf Med 2007; 46 (01) 43-49.
    Thieme ConnectPubMedSearch in Google Scholar
  • 9 Hozawa A. Attributable fractions of risk factors of cardiovascular diseases. Journal of Epidemiology 2011; 21 (02) 81-86.
    CrossrefPubMedSearch in Google Scholar
  • 10 Yusuf S, Hawken S, Öunpuu S, Dans T, Avezum A, Lanas F. et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries. The Lancet 2004; 364: 937-952.
    CrossrefPubMedSearch in Google Scholar
  • 11 Ramroth H, Dietz A, Becher H. Interaction effects and population-attributable risks for smoking and alcohol on laryngeal cancer and its subsites. A case-control study from Germany. Methods Inf Med 2004; 43 (05) 499-504.
    Thieme ConnectPubMedSearch in Google Scholar
  • 12 Levin ML. The occurrence of lung cancer in man. Acta Unio Int Contra Cancrum 1953; 9 (03) 531-541.
    PubMedSearch in Google Scholar
  • 13 Miettinen OS. Proportion of Disease caused or prevented by a given exposure, trait or intervention. American Journal of Epidemiology 1973; 99 (05) 325-332.
    PubMedSearch in Google Scholar
  • 14 Blankenberg S, Wild PS, Zeller T, Blettner M, Dugi KA, Lackner KJ. et al. Die Gutenberg Gesundheitsstudie. Bundesgesundheitsblatt 2012. Gesundheitsschutz 6/7 824-830.
    Search in Google Scholar
  • 15 Whitemore AS. Statistical methods for estimating attributable risks from retrospective data. Stat Med 1982; 1 (03) 229-243.
    CrossrefPubMedSearch in Google Scholar
  • 16 Shapley LS. Contributions to the theory of games II. Tucker AW, Kuhn HW. editors New Jersey: Press Princeton University; 1953
    Search in Google Scholar
  • 17 Gefeller O, Eide GE. Sequential and average attributable fractions as aids in the selection of preventive strategies. J Clin Epidemiol 1995; 48 (05) 645-655.
    CrossrefPubMedSearch in Google Scholar
  • 18 Rabe C, Gefeller O. The Attributable Risk in a Multifactorial Situation: Evaluation of Different Methods of Partitioning. Methods Inf Med 2006; 45 (04) 404-408.
    Thieme ConnectPubMedSearch in Google Scholar
  • 19 Land M, Vogel C, Gefeller O. Partitioning methods for multifactorial risk attribution. Statistical Methods in Medical Research 2001; 10 (03) 217-230.
    CrossrefPubMedSearch in Google Scholar
  • 20 Ezzati M, Hoorn SV, Rodgers A, Lopez AD, Mathers CD, Murray CJL. et al. Estimates of global and regional potential health gains from reducing multiple major risk factors. The Lancet 2003; 362 9380 271-280.
    CrossrefPubMedSearch in Google Scholar
  • 21 Lopez AD. The evolution of the Global Burden of Disease framework for disease, injury and risk factor quantification: developing the evidence base for national, regional and global public health action. Global Health 2005; 1 (01) 5
    CrossrefPubMedSearch in Google Scholar
  • 22 Gefeller O. An Annotated Bibliography on the Attributable Risk. Biometrical Journal 1992; 34 (08) 1007-1012.
    CrossrefPubMedSearch in Google Scholar
  • 23 Armitage P, Colton T. editors Encyclopedia of Biostatistics, New York: John Wiley & Sons; 2005
  • 24 Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G. et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European Heart Journal 2003; 24: 987-1003.
    CrossrefPubMedSearch in Google Scholar
  • 25 Federal Environment Agency (Germany), Federal Institute for Drugs and Medical Devices (Germany), Max Planck Institute of Psychiatry, Robert Koch Institute Germany National Health Interview and Examination Survey 1997-1999. Berlin, Germany: Robert Koch Institute; 2000
    Search in Google Scholar
  • 26 Bellach B-M. Editorial: Der Bundes-Gesundheitssurvey 1998- Erfahrungen, Ergebnisse, Perspektiven. Gesundheitswesen 61 (Sonderheft 2) Stuttgart: Thieme; 1999: 55-56.
    Search in Google Scholar
  • 27 Keil U, Fitzgerald AP, Gohlke H, Wellmann J, Hense HW. Risikoabschätzung tödlicher Herz-Kreislauf-Erkrankungen - Methoden. Deutsches Ärzteblatt 2005; 102 (25) A1-2.
    PubMedSearch in Google Scholar
  • 28 Law MR, Rodgers A. Lipids and cholesterol. In: Elliott P, Marmot M. editors Coronary Heart Disease Epidemiology: From aetiology to public health 2nd ed.. New York: Oxford University Press Inc.; 2005: 174-86.
    Search in Google Scholar