IDEAS home Printed from https://ideas.repec.org/p/dem/wpaper/wp-2002-003.html
   My bibliography  Save this paper

The influence of smoking and BMI on heritability in susceptibility to coronary heart disease

Author

Listed:
  • Andreas Wienke

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Anne M. Herskind
  • Kaare Christensen
  • Axel Skytthe
  • Anatoli I. Yashin

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

Cause-specific mortality data on Danish monozygotic (MZ) and dizygotic (DZ) twins are used to analyze the influence of smoking and body mass index (BMI) on heritability estimates of susceptibility to coronary heart disease (CHD). The sample includes 1209 like-sexed twin pairs born between 1890 and 1920, where both individuals were still alive and answered a questionnaire, including information about smoking, height and weight, in 1966. The analysis was conducted with both sexes pooled due to the relatively small number of twin pairs. Follow-up was conducted from 1 January 1966 to 31 December 1993. We use the correlated gamma-frailty model with observed covariates for the genetic analysis of frailty to account for censoring and truncation in the lifetime data. During the follow-up, 1437 deaths occurred, including 435 deaths due to CHD. Proportions of variance of frailty attributable to genetic and environmental factors were analyzed using the structural equation model approach. Different standard biometric models are fitted to the data to evaluate the magnitude and nature of genetic and environmental factors on mortality. Using the best fitting model without covariates, heritability of frailty to CHD was found to be 0.45 (0.11). This result changes only slightly to 0.54 (0.16) after controlling for smoking and BMI. This analysis underlines the existence of a substantial genetic influence on individual frailty associated with mortality caused by CHD. No evidence for common genetic factors acting on smoking, BMI, and susceptibility to CHD are found which indicates that the association between smoking and susceptibility to CHD and BMI and susceptibility to CHD is not confounded by common genetic factors.

Suggested Citation

  • Andreas Wienke & Anne M. Herskind & Kaare Christensen & Axel Skytthe & Anatoli I. Yashin, 2002. "The influence of smoking and BMI on heritability in susceptibility to coronary heart disease," MPIDR Working Papers WP-2002-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2002-003
    DOI: 10.4054/MPIDR-WP-2002-003
    as

    Download full text from publisher

    File URL: https://www.demogr.mpg.de/papers/working/wp-2002-003.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/MPIDR-WP-2002-003?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. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    2. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andreas Wienke, 2003. "Frailty models," MPIDR Working Papers WP-2003-032, Max Planck Institute for Demographic Research, Rostock, Germany.

    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. Bagdonavicius, Vilijandas & Nikulin, Mikhail, 2000. "On goodness-of-fit for the linear transformation and frailty models," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 177-188, April.
    2. Jiwon Lee & Midam An & Yongku Kim & Jung-In Seo, 2021. "Optimal Allocation for Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(18), pages 1-10, September.
    3. Benjamin G Schultz & Catherine J Stevens & Peter E Keller & Barbara Tillmann, 2013. "A Sequence Identification Measurement Model to Investigate the Implicit Learning of Metrical Temporal Patterns," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    4. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    5. Yahia Salhi & Pierre-Emmanuel Thérond, 2016. "Age-Specific Adjustment of Graduated Mortality," Working Papers hal-01391285, HAL.
    6. Feehan, Dennis & Wrigley-Field, Elizabeth, 2020. "How do populations aggregate?," SocArXiv 2fkw3, Center for Open Science.
    7. M. K. Lintu & Asha Kamath, 2022. "Performance of recurrent event models on defect proneness data," Annals of Operations Research, Springer, vol. 315(2), pages 2209-2218, August.
    8. Il Do Ha & Maengseok Noh & Youngjo Lee, 2010. "Bias Reduction of Likelihood Estimators in Semiparametric Frailty Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 307-320, June.
    9. Byrd, T. A. & Marshall, T. E., 1997. "Relating information technology investment to organizational performance: a causal model analysis," Omega, Elsevier, vol. 25(1), pages 43-56, February.
    10. Filipe Costa Souza & Wilton Bernardino & Silvio C. Patricio, 2024. "How life-table right-censoring affected the Brazilian social security factor: an application of the gamma-Gompertz-Makeham model," Journal of Population Research, Springer, vol. 41(3), pages 1-38, September.
    11. Svetlana V. Ukraintseva & Anatoli I. Yashin, 2005. "Economic progress as cancer risk factor. I: Puzzling facts of cancer epidemiology," MPIDR Working Papers WP-2005-021, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, vol. 64(3), pages 625-633, January.
    13. Nicos Nicolaou & Scott Shane, 2019. "Common genetic effects on risk-taking preferences and choices," Journal of Risk and Uncertainty, Springer, vol. 59(3), pages 261-279, December.
    14. Stephen Richards, 2010. "Author's response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(4), pages 920-924, October.
    15. Silke van Daalen & Hal Caswell, 2015. "Lifetime reproduction and the second demographic transition: Stochasticity and individual variation," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(20), pages 561-588.
    16. Ken B Hanscombe & Maciej Trzaskowski & Claire M A Haworth & Oliver S P Davis & Philip S Dale & Robert Plomin, 2012. "Socioeconomic Status (SES) and Children's Intelligence (IQ): In a UK-Representative Sample SES Moderates the Environmental, Not Genetic, Effect on IQ," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-16, February.
    17. K. Motarjem & M. Mohammadzadeh & A. Abyar, 2020. "Geostatistical survival model with Gaussian random effect," Statistical Papers, Springer, vol. 61(1), pages 85-107, February.
    18. Schultz, T. Paul, 2010. "Population and Health Policies," Handbook of Development Economics, in: Dani Rodrik & Mark Rosenzweig (ed.), Handbook of Development Economics, edition 1, volume 5, chapter 0, pages 4785-4881, Elsevier.
    19. Xu, Linzhi & Zhang, Jiajia, 2010. "An EM-like algorithm for the semiparametric accelerated failure time gamma frailty model," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1467-1474, June.
    20. Zhang, Quanzhong & Wei, Haiyan & Liu, Jing & Zhao, Zefang & Ran, Qiao & Gu, Wei, 2021. "A Bayesian network with fuzzy mathematics for species habitat suitability analysis: A case with limited Angelica sinensis (Oliv.) Diels data," Ecological Modelling, Elsevier, vol. 450(C).

    More about this item

    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:wpaper:wp-2002-003. 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: Peter Wilhelm (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.