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Journal of Semnan University of Medical Sciences

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Outlines

Predictive factors of glycosylated hemoglobin using additive regression model

Author(s):
Hamzeh ZangenehHamzeh Zangeneh, Mehdi OmidiMehdi Omidi, Marzieh HadaviMarzieh Hadavi, Hossein SeidkhaniHossein SeidkhaniHossein Seidkhani ORCID, Kourosh SayehmiriKourosh Sayehmiri,*
Koomesh:Vol. 23, issue 3; 402-408
Published online:Aug 02, 2021
Article type:Research Article
Received:Aug 01, 2020
Accepted:Nov 02, 2020
How to Cite:Zangeneh H, Omidi M, Hadavi M, Seidkhani H, Sayehmiri K. Predictive factors of glycosylated hemoglobin using additive regression model. koomesh. 2021;23(3):e149960. doi:

Abstract

Keywords
Diabetes Mellitus
Glycated Hemoglobin A
Body Mass Index
Waist Circumference
Regression Analysis
دیابت شیرین
هموگلوبین گلیکوزیله
شاخص توده بدنی
دور کمر
آنالیز رگرسیون

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  • 33.
    [2] Trasoff D, Delizo J, Du B, Purnajo C, and Morales J. Diabetes in the Middle East. Epinex Diagnostics, Inc. Corporate Information Series -4, 2008. Available from: URL: http://www.epinex.com/pdf/Epinex_Diabetes_ MidEast.pdf. [Accessed date: 2009/04/20].
  • 34.
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  • 35.
    [4] Mohammedi K, Woodward M, Hirakawa Y, Zoungas S, Colagiuri S, Hamet P, et al. Microvascular and macrovascular disease and risk for major peripheral arterial disease in patients with type 2 diabetes. Diabetes Care 2016; 39: 1796-1803.
  • 36.
    https://doi.org/10.2337/dc16-1594.
  • 37.
    https://doi.org/10.2337/dc16-0588.
  • 38.
    PMid:27456835.
  • 39.
    [5] Ghafari M, Rakhshanderou S, Heidarnia A, Rajab A. The effectiveness of educational interventions on metabolic control in diabetic patients referred to Iranian Diabetes Association. Iran J Diabet Lipid 2009; 57-64. (Persian).
  • 40.
    [6] International Diabetes Federation. IDF Diabetes Atlas. Online International Diabetes Federation. 2015. Available from: URL: https://www.idf.org/e-library/epidemiology-research/diabetes-atlas/13-diabetes-atlasseventh-edition.html.
  • 41.
    [7] Jafari-Shobeiri M, Ghojazadeh M, Azami-Aghdash S, Naghavi-Behzad M, Piri R, Pourali-Akbar Y, et al. Prevalence and risk factors of gestational diabetes in Iran: a systematic review and meta-analysis. Iran J Public Health 2015; 44: 1036-1044.
  • 42.
    [8] Peters KE, Chubb SA, Davis WA, Davis TM. The relationship between hypomagnesemia, metformin therapy and cardiovascular disease complicating type 2 diabetes: the fremantle diabetes study. PLoS One 2013; 8: e74355.
  • 43.
    https://doi.org/10.1371/journal.pone.0074355.
  • 44.
    PMid:24019966 PMCid:PMC3760872.
  • 45.
    [9] Friedman JH, Stuetzle W. Projection pursuit regression. J Am Statis Assoc 1981; 76: 817-823.
  • 46.
    https://doi.org/10.1080/01621459.1981.10477729.
  • 47.
    [10] Vazirinasab H, Salehi M, Khoshgam M, Rafati N. Comparison of generalized additive models and generalized linear models for estimating the retinopathy risk factors for diabetic patients in Tehran. JNKUMS. 2014; 5: 849-858. (Persian).
  • 48.
    https://doi.org/10.29252/jnkums.5.4.849.
  • 49.
    [11] Mohammadi B, Hassanzadeh A. Analysis of risk factors for type 2 diabetes mellitus using response surface methodology. JSSU 2011; 19: 655-666 (Persian).
  • 50.
    [12] Esmailnasab N, Afkhamzadeh A, Ebrahimi A. Effective factors on diabetes control in Sanandaj diabetes center. IRJE 2010; 6: 39-45 (Persian).
  • 51.
    [13] Danaei N, Tamadon M, Monsan M. Evaluation of diabetes control and some related factors in patients of diabetes clinic of semnan fatemieh hospital. Koomesh 2004; 6: 31-36. (Persian).
  • 52.
    [14] Mahdavi M, mehrabi Y, khalili D, baghestani A R, bagherzadeh khiabani F, mansoori S. Factors associated with incidence of type II diabetes in pre-diabetic women using Bayesian Model Averaging. Koomesh 2017; 19: 591-602: (Persian).
  • 53.
    [15] Ghadiri-Anari A, Kheirollahi K, Hazar N, Mohiti Ardekani A, kharazmi S, Namiranian N, et al. Prevalence of risk factors in diabetic patients with oral complications. Koomesh 2019; 21: 477-485: (Persian).
  • 54.
    [16] Brooks Gordon P, Barcikowski Robert S. The PEAR method for sample sizes in multiple linear regression. Multiple Linear Regression Viewpoints 2012; 38.
  • 55.
    [17] Mohammadi B, Hassanzadeh A. Analysis of risk factors for type 2 diabetes mellitus using response surface methodology. JSSU 2011; 19: 655-666 (Persian0.
  • 56.
    [18] Hastie TR. Tibshirani. Generalized Additive Model. Stat Science 1986; 1: 297-318.
  • 57.
    https://doi.org/10.1214/ss/1177013604.
  • 58.
    [19] Hastie TR. Tibshirani. Non-parametric logistic and proportional odds regression. Appl Stat 1990; 260-276.
  • 59.
    https://doi.org/10.2307/2347785.
  • 60.
    [20] Khatri namani Z, Bakhshi E, Naghipour A, Hossein Zadeh S. Assessment of hemoglobin A1C in patients with type 2 diabetes in the first three years of care and its related factors. JHPM 2017; 6: 34-42 (Persian).
  • 61.
    https://doi.org/10.21859/jhpm-07035.
  • 62.
    [21] Oscar Lado Baleato, Bivariate copular regression models in diabetes research, Master Thesis, univeside. De Santiago 2016-2017.

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