IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v11y2014i10p10663-10693d41233.html
   My bibliography  Save this article

Longitudinal Trajectories of Cholesterol from Midlife through Late Life according to Apolipoprotein E Allele Status

Author

Listed:
  • Brian Downer

    (Sealy Center on Aging, University of Texas Medical Branch, 301 University Blvd., Galveston, TX 77555, USA)

  • Steven Estus

    (Department of Physiology, College of Medicine, University of Kentucky, 138 Leader Avenue, Lexington, KY 40506, USA
    Sanders-Brown Center on Aging, University of Kentucky, 101 Sanders-Brown Building, 800 S. Limestone Street, Lexington, KY 40536, USA)

  • Yuriko Katsumata

    (Department of Biostatistics, College of Public Health, University of Kentucky, Suite 205, 725 Rose Street, Lexington, KY 40536, USA)

  • David W. Fardo

    (Sanders-Brown Center on Aging, University of Kentucky, 101 Sanders-Brown Building, 800 S. Limestone Street, Lexington, KY 40536, USA
    Department of Biostatistics, College of Public Health, University of Kentucky, Suite 205, 725 Rose Street, Lexington, KY 40536, USA)

Abstract

Background: Previous research indicates that total cholesterol levels increase with age during young adulthood and middle age and decline with age later in life. This is attributed to changes in diet, body composition, medication use, physical activity, and hormone levels. In the current study we utilized data from the Framingham Heart Study Original Cohort to determine if variations in apolipoprotein E ( APOE ), a gene involved in regulating cholesterol homeostasis, influence trajectories of total cholesterol, HDL cholesterol, and total: HDL cholesterol ratio from midlife through late life. Methods: Cholesterol trajectories from midlife through late life were modeled using generalized additive mixed models and mixed-effects regression models. Results : APOE e2+ subjects had lower total cholesterol levels, higher HDL cholesterol levels, and lower total: HDL cholesterol ratios from midlife to late life compared to APOE e3 and APOE e4+ subjects. Statistically significant differences in life span cholesterol trajectories according to gender and use of cholesterol-lowering medications were also detected. Conclusion: The findings from this research provide evidence that variations in APOE modify trajectories of serum cholesterol from midlife to late life. In order to efficiently modify cholesterol through the life span, it is important to take into account APOE allele status.

Suggested Citation

  • Brian Downer & Steven Estus & Yuriko Katsumata & David W. Fardo, 2014. "Longitudinal Trajectories of Cholesterol from Midlife through Late Life according to Apolipoprotein E Allele Status," IJERPH, MDPI, vol. 11(10), pages 1-31, October.
    • Handle: RePEc:gam:jijerp:v:11:y:2014:i:10:p:10663-10693:d:41233
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/11/10/10663/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/11/10/10663/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Weijenberg, M.P. & Feskens, E.J.M. & Kromhout, D., 1996. "Age-related changes in total and high-density-lipoprotein cholesterol in elderly Dutch men," American Journal of Public Health, American Public Health Association, vol. 86(6), pages 798-803.
    2. Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
    3. X. Lin & D. Zhang, 1999. "Inference in generalized additive mixed modelsby using smoothing splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 381-400, April.
    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. Simon N. Wood, 2006. "Low-Rank Scale-Invariant Tensor Product Smooths for Generalized Additive Mixed Models," Biometrics, The International Biometric Society, vol. 62(4), pages 1025-1036, December.
    2. Brezger, Andreas & Lang, Stefan, 2006. "Generalized structured additive regression based on Bayesian P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 967-991, February.
    3. Belitz, Christiane & Lang, Stefan, 2008. "Simultaneous selection of variables and smoothing parameters in structured additive regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 61-81, September.
    4. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
    5. Lawrence N Kazembe & Placid M G Mpeketula, 2010. "Quantifying Spatial Disparities in Neonatal Mortality Using a Structured Additive Regression Model," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-10, June.
    6. Nadja Klein & Michel Denuit & Stefan Lang & Thomas Kneib, 2013. "Nonlife Ratemaking and Risk Management with Bayesian Additive Models for Location, Scale and Shape," Working Papers 2013-24, Faculty of Economics and Statistics, Universität Innsbruck.
    7. Xiaojun Xu & Fengfeng Ma & Kangying Lu & Baoqi Zhu & Shuaichen Li & Kangqi Liu & Qianmin Chen & Qingfen Li & Cheng Deng, 2023. "Estimation of Biomass Dynamics and Allocation in Chinese Fir Trees Using Tree Ring Analysis in Hunan Province, China," Sustainability, MDPI, vol. 15(4), pages 1-14, February.
    8. Rodríguez-Álvarez, María Xosé & Lee, Dae-Jin & Kneib, Thomas & Durbán, María & Eilers, Paul, 2013. "Fast algorithm for smoothing parameter selection in multidimensional generalized P-splines," DES - Working Papers. Statistics and Econometrics. WS ws133026, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Klein, Nadja & Denuit, Michel & Lang, Stefan & Kneib, Thomas, 2013. "Nonlife Ratemaking and Risk Management with Bayesian Additive Models for Location, Scale and Shape," LIDAM Discussion Papers ISBA 2013045, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Denuit, Michel & Lang, Stefan, 2004. "Non-life rate-making with Bayesian GAMs," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 627-647, December.
    11. M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.
    12. Iñaki Galán & Lorena Simón & Elena Boldo & Cristina Ortiz & Rafael Fernández-Cuenca & Cristina Linares & María José Medrano & Roberto Pastor-Barriuso, 2017. "Changes in hospitalizations for chronic respiratory diseases after two successive smoking bans in Spain," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
    13. Longhi, Christian & Musolesi, Antonio & Baumont, Catherine, 2014. "Modeling structural change in the European metropolitan areas during the process of economic integration," Economic Modelling, Elsevier, vol. 37(C), pages 395-407.
    14. Strasak, Alexander M. & Umlauf, Nikolaus & Pfeiffer, Ruth M. & Lang, Stefan, 2011. "Comparing penalized splines and fractional polynomials for flexible modelling of the effects of continuous predictor variables," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1540-1551, April.
    15. Schwemmer, Philipp & Güpner, Franziska & Adler, Sven & Klingbeil, Knut & Garthe, Stefan, 2016. "Modelling small-scale foraging habitat use in breeding Eurasian oystercatchers (Haematopus ostralegus) in relation to prey distribution and environmental predictors," Ecological Modelling, Elsevier, vol. 320(C), pages 322-333.
    16. Soutik Ghosal & Timothy S. Lau & Jeremy Gaskins & Maiying Kong, 2020. "A hierarchical mixed effect hurdle model for spatiotemporal count data and its application to identifying factors impacting health professional shortages," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1121-1144, November.
    17. Damien Rousselière, 2019. "A Flexible Approach to Age Dependence in Organizational Mortality: Comparing the Life Duration for Cooperative and Non-Cooperative Enterprises Using a Bayesian Generalized Additive Discrete Time Survi," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 829-855, December.
    18. Ferraccioli, Federico & Sangalli, Laura M. & Finos, Livio, 2022. "Some first inferential tools for spatial regression with differential regularization," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    19. Ding, Hui & Zhang, Jian & Zhang, Riquan, 2022. "Nonparametric variable screening for multivariate additive models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    20. Abdollah Jalilian, 2017. "Modelling and classification of species abundance: a case study in the Barro Colorado Island plot," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2401-2409, October.

    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:gam:jijerp:v:11:y:2014:i:10:p:10663-10693:d:41233. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.