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Volume 15, Issue 2 (3-2017)
IJRM 2017, 15(2): 109-114 |
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Abbasi M, Mazloum Khorasani Z, Etminani K, Rahmanvand R. Determination of the most important risk factors of gestational diabetes in Iran by group analytical hierarchy process (GAHP). IJRM 2017; 15 (2) :109-114
URL: http://ijrm.ir/article-1-797-en.html
URL: http://ijrm.ir/article-1-797-en.html
1- Research Committee, Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
2- Endocrine Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
3- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. , EtminaniK@mums.ac.ir
4- Islamic Azad University, South Tehran Branch, Tehran, Iran.
2- Endocrine Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
3- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. , EtminaniK@mums.ac.ir
4- Islamic Azad University, South Tehran Branch, Tehran, Iran.
Abstract: (3277 Views)
Background: The outbreak of gestational diabetes has a significant increase during 14 recent years. This disease has complications for mother and her baby. Screening is an opportunity for preventing of gestational diabetes it's complications.
Objective: The aim of this research was to determine the most important risk factors of gestational diabetes mellitus (GDM) in Iran according to the expert's views by Group Analytical Hierarchy Process.
Materials and Methods: In this cross-sectional study, papers related to the prevalence and risk factors of GDM in Iran from 1992-2015 were reviewed. By studying texts and Upto Date databases, 10 risk factors of gestational diabetes were collected. Among these 10 items, the risk factors that have become significant based on studying literature in Iran were selected for analysis. GAHP questionnaire distributed among all experts.
Results: 8 risk factors of gestational diabetes were significant in Iran. The analysis of experts' views showed that "History of GDM or disorder in glucose tolerance in pregnancy" is the most important risk factor for developings GDM (40.7%). The second and third most important risk factors were "History of macrosomia (infant birth (weight > 4.1 Kg)" (20.2%) and" History of diabetes in first degree relatives " (10.7%).
Conclusion: Correct knowledge of prevalence of gestational diabetes and its risk factors is necessary for effective planning. SuggestSuggesting screening based on the importance of these risk factors can reduce the cost and stress in pregnant women. Also, it makes faster patient identifying faster.
Objective: The aim of this research was to determine the most important risk factors of gestational diabetes mellitus (GDM) in Iran according to the expert's views by Group Analytical Hierarchy Process.
Materials and Methods: In this cross-sectional study, papers related to the prevalence and risk factors of GDM in Iran from 1992-2015 were reviewed. By studying texts and Upto Date databases, 10 risk factors of gestational diabetes were collected. Among these 10 items, the risk factors that have become significant based on studying literature in Iran were selected for analysis. GAHP questionnaire distributed among all experts.
Results: 8 risk factors of gestational diabetes were significant in Iran. The analysis of experts' views showed that "History of GDM or disorder in glucose tolerance in pregnancy" is the most important risk factor for developings GDM (40.7%). The second and third most important risk factors were "History of macrosomia (infant birth (weight > 4.1 Kg)" (20.2%) and" History of diabetes in first degree relatives " (10.7%).
Conclusion: Correct knowledge of prevalence of gestational diabetes and its risk factors is necessary for effective planning. SuggestSuggesting screening based on the importance of these risk factors can reduce the cost and stress in pregnant women. Also, it makes faster patient identifying faster.
Type of Study: Original Article |
References
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43. Group THSCR. Hyperglycemia and Adverse Pregnancy Outcomes. Diabetes 2009; 58: 453-459.
44. Ferrara A. Increasing Prevalence of Gestational Diabetes Mellitus A public health perspective. Diabetes Care 2007; 30: 141-146.
45. Yumei W, Huixia Y, Weiwei Z, Hongyun Y, Haixia L, Jie Y, et al. International Association of Diabetes and Pregnancy Study Group criteria is suitable for gestational diabetes mellitus diagnosis: further evidence from China. Chin Med J 2014; 127: 3553-3556.
46. Hillier TA, Pedula KL, Schmidt MM, Mullen JA, Charles M-A, Pettitt DJ. Childhood Obesity and Metabolic Imprinting. Diabetes Care 2007; 30: 2287-2292.
47. Moyer VA. Screening for Gestational Diabetes Mellitus: U.S. Preventive Services Task Force Recommendation Statement. Ann Intern Med 2014; 160: 414-420.
48. Arora D, Arora R, Sangthong S, Leelaporn W, Sangratanathongchai J. Universal screening of gestational diabetes mellitus: prevalence and diagnostic value of clinical risk factors. J Med Assoc Thai 2013; 96: 266-271.
49. Keshavarz M, Cheung NW, Babaee GR, Moghadam HK, Ajami ME, Shariati M. Gestational diabetes in Iran: incidence, risk factors and pregnancy outcomes. Diabetes Res Clin Pract 2005; 69: 279-286.
50. Miailhe Gg, Kayem G, Girard G, Legardeur H, Mandelbrot L. Selective rather than universal screening for gestational diabetes mellitus? Eur J Obstet Gynecol Reprod Biol 2015; 191: 95-100.
51. Leeuwen Mv, Opmeer BC, Zweers EJK, Ballegooie Ev, Brugge HGt, Valk HWd, et al. Estimating the risk of gestational diabetes mellitus: a clinical prediction model based on patient characteristics and medical history. Int J Obstet Gynaecol 2010; 117: 69-75.
52. Goli M, Firouzeh F. Prevalence of gestational diabetes and efficacy of risk factors in screening of referrals to health centers. Holistic Nurs Midwif J 2013; 24: 56-63.
53. Rahimi G. The prevalence of gestational diabetes in pregnant women referred Health Ardebil city. Res Sci J Ardabil Univ Med Sci 2004; 4: 32-38.
54. Vakili M, Pordanjani SR, Alipor N, Taheri M, Baeradeh N, Hashemi AA. The prevalence of gestational diabetes and associated factors in pregnant women referred to health care centers of Yazd in 2012. J Sabzevar Univ Med Sci 2015; 21: 1214-1224.
55. Srdjevic B, Srdjevic Z, Blagojevic B, Suvocarev K. A two-phase algorithm for consensus building in AHP-group decision making. Appl Mathemat Model 2013; 37: 6670-6682.
56. AsgharPour MJ. Multi Attribute Decision Making. Multi Criteria Decision Making. Tehran, University of Tehran Press; 2008: 191-319.
57. Liberatore MJ, Nydick RL. The analytic hierarchy process in medical and health care decision making: A literature review. Eur J Operat Res 2008; 189: 194-207.
58. Lu GC, Luchesse A, Chapman V, Cliver S, Rouse DJ. Screening for gestational diabetes mellitus in the subsequent pregnancy: is it worthwhile? Am J Obstet Gynecol 2002; 187: 918-921.
59. Baron M. Introduction to Statistics. Probability and Statistics for Computer Scientists. 2nd Ed. Taylor and Francis Group, 2014: 208-233.
60. Huvinena E, Grotenfeltb NE, Erikssonbcd JG, Rönöa K, Klemettiaef MM, Roinegh R, et al. Heterogeneity of maternal characteristics and impact on gestational diabetes (GDM) risk-Implications for universal GDM screening? Annal Med 2016; 48: 52-58.
61. Fawole AO, Ezeasor C, Bello F, Roberts A, Awoyinka B, Tongo O, et al. Effectiveness of a structured checklist of risk factors in identifying pregnant women at risk of gestational diabetes mellitus: A cross-sectional study. Nigerian J Clin Pract 2014; 17: 495-501.
62. Perkins JM, Dunn JP, Jagasia SM. Perspectives in Gestational Diabetes Mellitus: A Review of Screening, Diagnosis, and Treatment. Clin Diabetes 2007; 25: 57-62.
63. Khoushideh M, SHahriari A. Comparison of universal and risk factor based screening strategies for gestational diabetes mellitus. SHiraz E-Med J 2008; 9: 24-29.
64. Tabatabaei A, Fallah Z, Haghighi S, Farmani M, Horri N, Eslamian Z, et al. Prevalence and Risk Factors for Gestational Diabetes Mellitus in Pregnant Women of Isfahan, Iran. IJEM 2007; 9: 251-259.
65. Hedayati H, Khazaee T, Mogharrab M, Sharifzadeh GR. Prevalence of gestational diabetes mellitus and overt diabetes in perganant women in Birjand. mod-care-J 2012; 8: 238-244.
66. Teh WT, Teede HJ, Paul E, Harrison CL, Wallace EM, Allan C. Risk factors for gestational diabetes mellitus: implications for the application of screening guidelines. Aust N Z J Obstet Gynaecol 2011; 51: 26-30.
67. Shirazian N, Emdadi R, Mahboubi M, Motevallian A, Fazel-Sarjuei Z, Sedighpour N, et al. Screening for gestational diabetes: usefulness of clinical risk factors. Arch Gynecol Obstet 2009; 280: 933-937.
68. Bouzari Z, Yazdani S, Samakoosh MA, Nataj MM, Meibodi SE. Prevalence of Gestational Diabetes and Its Risk Factors in Pregnant Women Referred to Health Centers of Babol, Iran, from September 2010 to March 2012. Iran J Obstet Gynecol Infertil 2013; 16: 6-13.
69. Larijani B, Azizi F, Bastanhagh M, Pajouhi M, Hoseinnezadeh A. The prevalence of gestational diabetes mellitus in young women. Iran J Endocrinol Metab 2002; 4: 23-27.
70. Keshavarz M, Babaee GHR. The risk factors for GDM and the value of the screening test. Iran J Endocrinol Metab 2004; 6: 331-336.
71. Nikoo MK, Ahranjani SA, Larijani B. A review on the prevalence of gestational diabetes mellitus (GDM) in different regions of Iran. J Diabetes Metab Disord 2009; 8.
72. Abdullah L, Azman FN. Weights of Obesity Factors Using Analytic Hierarchy Process. IJRRAS 2011; 7: 57-63.
73. Maranate T, Pongpullponsak A, Ruttanaumpawan P. The Prioritization of Clinical Risk Factors of Obstructive Sleep Apnea Severity Using Fuzzy Analytic Hierarchy Process. Comp Mathemat Methods Med 2015; 2015.
74. Pecchia L, Martin JL, Ragozzino A, Vanzanella C, Scognamiglio A, Mirarchi L, et al. User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner. BMC Med Informat Decision Mak 2013; 13: 1-11.
75. Danner M, Hummel JM, Volz F, Manen JGv, Wiegard B, Dintsios C-M, et al. Integrating patients’ views into health technology assessment: Analytic hierarchy process (AHP) as a method to elicit patient preferences. Int J Technol Assess Health Care 2011; 27: 1-4.
76. Hilgerink MP, Hummel JM, Manohar S, Vaartjes SR, Ijzerman MJ. Assessment of the added value of the Twente Photoacoustic Mammoscope in breast cancer diagnosis. Med Devices: Evidence Res 2011; 4: 107-115.
77. Suner A, Celikoglu CC, Dicle O, Sokmen S. Sequential decision tree using the analytic hierarchy process for decision support in rectal cancer. Artif Intell Med 2012; 56: 59-68.
78. Schmidt K, Aumann I, Hollander I, Damm K, Schulenburg J-MGvd. Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting. BMC Med Informat Decision Mak 2015; 15: 1-27.
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