IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v28y2013i7.html
   My bibliography  Save this article

Application of the modified PGW method for determining the smoking attributable fraction of deaths in New Zealand Maori, Pacific and non-Maori non-Pacific populations

Author

Listed:
  • Peter Sandiford

    (Waitemata District Health Board)

  • Dale Bramley

    (Waitemata District Health Board)

Abstract

Background: Preston, Glei and Wilmoth recently proposed a new method for estimating smoking-attributable mortality in high income countries and an improvement to the method was proposed by Rostron. The method greatly simplifies estimation of smoking attributable fractions but additional testing has been recommended to validate the approach. Objective: We apply the Rostron (PGW-R) method to ethnic groups in New Zealand and compare the results with published estimates from other sources with the purpose of determining their consistency and exploring possible reasons for any divergence. Methods: Four different sources were identified with ethnic-specific estimates of smoking attributable mortality fractions (SAMF)for Maori, Pacific Island and European/Other ethnic groups in New Zealand for periods between 1995 and 1999. These employed a variety of direct and indirect estimation techniques. The results were compared with PGW-R method estimates for the same period and ethnic groups. Results: Although the PGW-R method produced SAMF estimates that were within 5% of those derived using the Peto-Lopez method for the European/other and total populations (in males and females), there were significant discrepancies between them in the Maori and Pacific SAMF estimates. Results using direct methods from a census linkage study were inconsistent with both the Peto-Lopez and the PGW-R method. Seven possible explanations for these discrepancies were considered and discussed but none could fully account for the differences. Conclusions: The results of this work raise questions not only about the validity of the PGW-R method, but also about the accuracy of the estimates derived from the Peto-Lopez and direct methods, at least in these populations. Further research should examine the applicability of the key assumptions of the PGW method. Other work to determine the effects of possible misclassification bias in the direct method estimates would also aid interpretation of these findings. Until then it would be prudent to use the PGW-R method cautiously when examining ethnic differences in SAMF. Comments: Accurate methods for determining the population health impact of smoking are vital for policy-makers to ensure that tobacco control is awarded the appropriate emphasis and resourcing.

Suggested Citation

  • Peter Sandiford & Dale Bramley, 2013. "Application of the modified PGW method for determining the smoking attributable fraction of deaths in New Zealand Maori, Pacific and non-Maori non-Pacific populations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(7), pages 207-228.
    • Handle: RePEc:dem:demres:v:28:y:2013:i:7
    DOI: 10.4054/DemRes.2013.28.7
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol28/7/28-7.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/DemRes.2013.28.7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Percy, C. & Stanek III, E. & Gloeckler, L., 1981. "Accuracy of cancer death certificates and its effect on cancer mortality statistics," American Journal of Public Health, American Public Health Association, vol. 71(3), pages 242-250.
    2. Brian L. Rostron, 2010. "A modified new method for estimating smoking-attributable mortality in high-income countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 23(14), pages 399-420.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Konrad Samsel & Tanya Navaneelan & Nathan DeBono & Louis Everest & Paul A. Demers & Jeavana Sritharan, 2024. "Leukemia Incidence by Occupation and Industry: A Cohort Study of 2.3 Million Workers from Ontario, Canada," IJERPH, MDPI, vol. 21(8), pages 1-16, July.
    2. Tobias C. Vogt & Alyson A. van Raalte & Pavel Grigoriev & Mikko Myrskylä, 2016. "German East-West mortality difference: two cross-overs driven by smoking," MPIDR Working Papers WP-2016-004, Max Planck Institute for Demographic Research, Rostock, Germany.
    3. Jessica Ho & Irma Elo, 2013. "The Contribution of Smoking to Black-White Differences in U.S. Mortality," Demography, Springer;Population Association of America (PAA), vol. 50(2), pages 545-568, April.
    4. F. Peters & J. P. Mackenbach & W. J. Nusselder, 2016. "Does the Impact of the Tobacco Epidemic Explain Structural Changes in the Decline of Mortality?," European Journal of Population, Springer;European Association for Population Studies, vol. 32(5), pages 687-702, December.
    5. Angela B Mariotto & Zhaohui Zou & Christopher J Johnson & Steve Scoppa & Hannah K Weir & Bin Huang, 2018. "Geographical, racial and socio-economic variation in life expectancy in the US and their impact on cancer relative survival," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    6. Andrew Fenelon & Samuel Preston, 2012. "Estimating Smoking-Attributable Mortality in the United States," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 797-818, August.
    7. Fanny Janssen & Leo Wissen & Anton Kunst, 2013. "Including the Smoking Epidemic in Internationally Coherent Mortality Projections," Demography, Springer;Population Association of America (PAA), vol. 50(4), pages 1341-1362, August.
    8. Soetewey, Antoine & Legrand, Catherine & Denuit, Michel & Silversmit, Geert, 2023. "Health indices for disease incidence and duration in the Semi-Markov setting," LIDAM Discussion Papers ISBA 2023013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Joseph T. Lariscy & Robert A. Hummer & Richard G. Rogers, 2018. "Cigarette Smoking and All-Cause and Cause-Specific Adult Mortality in the United States," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1855-1885, October.
    10. Fanny Janssen & Alette Spriensma, 2012. "The contribution of smoking to regional mortality differences in the Netherlands," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 27(9), pages 233-260.
    11. Alicia Villavicencio & Marta Solans & Lluís Zacarías-Pons & Anna Vidal & Montse Puigdemont & Josep Maria Roncero & Marc Saez & Rafael Marcos-Gragera, 2021. "Comorbidities at Diagnosis, Survival, and Cause of Death in Patients with Chronic Lymphocytic Leukemia: A Population-Based Study," IJERPH, MDPI, vol. 18(2), pages 1-10, January.
    12. Tobias Vogt & Alyson van Raalte & Pavel Grigoriev & Mikko Myrskylä, 2017. "The German East-West Mortality Difference: Two Crossovers Driven by Smoking," Demography, Springer;Population Association of America (PAA), vol. 54(3), pages 1051-1071, June.
    13. Binbing Yu & Lan Huang & Ram C. Tiwari & Eric J. Feuer & Karen A. Johnson, 2009. "Modelling population‐based cancer survival trends by using join point models for grouped survival data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 405-425, April.
    14. Alyson van Raalte & Mikko Myrskylä & Pekka Martikainen, 2015. "The role of smoking on mortality compression," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(20), pages 589-620.

    More about this item

    Keywords

    smoking-related mortality; tobacco use; PGW method; Peto-Lopez method; lung cancer; cannabis smoking;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dem:demres:v:28:y:2013:i:7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.