Volume 15, Issue 2 (3-2017)                   IJRM 2017, 15(2): 109-114 | Back to browse issues page


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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
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.
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Introduction
 
Gestational diabetes is developed in the pregnant women in whom pancreas function is not enough to overcome resistance to insulin (1). The outbreak of this complication has a significant increase during recent years (2). The prevalence of gestational diabetes has been estimated 3.4% in Iran (3). High level of mother’s blood sugar is followed by complications for mother and her baby (4). About 50% of the women suffered from gestational diabetes, will be suffered from type 2 diabetes during 5 years after pregnancy (5, 6). There is a relationship between increased blood sugar during pregnancy and children’s obesity at age of 5-7 years (7), infant macrosomia and mother's caesarean (4,6).
Screening for treating gestational diabetes is an opportunity for preventing the complications of it (8). The main problem in public screening is cost effectiveness (9). This cost is an important issue for many Asian countries. According to a study conducted in 2005, the cost of a general screening in Iran has been calculated to be the US $2.50 for Glucose Challenge Test (GCT) and the US $7.50 for Glucose Tolerance Test (GTT) (10). The main issue in selective screening is the international disagreement on risk factors (11). Several international specialized groups have suggested using risk factors to identify the women at risk of gestational diabetes (12). The studies conducted in Iran have shown various factors as the most important risk factors for gestational diabetes (13-15).
One of the effective and appropriate methods for group decision-making to determine the most important factors and rank them is the Group Analytical Hierarchy Process (GAHP) (16). This method is one of the most famous techniques of Multi-Attribute Decision Making (MADM) presented by Saaty in 1970 for the first time. For decision-making, firstly, hierarchy structure of criteria and alternatives is created and then paired comparisons are performed among criteria. In calculating these comparisons, the weight of each criterion and their priorities are specified (17).
In the last 10 years, using this method is clearly increasing in health care and medical decision-making. According to a systematic review conducted, this trend increased 20% from 2002 to 2016, which 12% of it is related to the last two years. This method is used in a wide range of medical and health care decision-making such as assessing and selecting care and treatment methods and assessing technology and policies of health care (18). Risk factors related to gestational diabetes are largely derived from studies on European populations(19), and a few studies have tested them in other populations (10).
This research aims at deriving risk factors of gestational diabetes from literature and determining the importance of these risk factors in Iran according to the experts' views by GAHP.
 
Materials and methods
 
Questionnaire
The questionnaire of the Analytical Hierarchy Process (AHP( was developed using a 9 points scale (Table I). In the AHP created on paired comparisons, for n criteria, the number of these comparisons is n (n-1)/2. Therefore according to the 8 criteria in this study, the total numbers of questions for paired comparisons among criteria were 28.
 
Procedure
In this cross-sectional study, firstly, the papers related to the study of the prevalence and risk factors of gestational diabetes in Iran from 1992-2015 were reviewed. In this study, 27 papers related to the prevalence of gestational diabetes and its risk factors were extracted. By studying texts and Up to Date database, 10 risk factors for gestational diabetes were collected. Among these 10 items, the risk factors that have become significant based on studying literature in Iran were selected for performing the analysis process (1).
This list includes 8 risk factors of gestational diabetes that have been presented in table II. The two risk factors of ethnicity and mother's weight at birth have not been examined in Iran and thus were omitted. In the process of AHP, to perform paired comparisons, the researches distributed questionnaire among all the population of research. The populations at this research were endocrinology experts of Mashhad, Iran. After following up in some phases, 11 experts completed the questionnaire. For each questionnaire, a paired comparisons matrix was formed and then the matrices were normalized using the following formula:


To calculate the consistency ratio of comparisons of each expert, consistency index (CI) of each matrix was calculated by the following question:

λmax is the largest eigenvector of paired comparison matrix and n is the number of criteria. Then, Consistency Ratio (CR) was calculated using this formula: 

RI is consistency index obtained from the pared comparison matrix that has been generated randomly (Table III). In this study, the numbers of criteria are 8, so (RI) value is 1.41. Consistency Ratio means that there is an acceptable contradiction in response to the questions. According to the literature, If CR is <0.1 for any matrix, consistency of answers is acceptable. Two questionnaires have CR higher than 0.1 and were excluded from the rest of calculations. The 9 remained questionnaires having acceptable consistency were entered group calculation. In the next step, the weight of any risk factor was calculated according to each expert's views using the following equation:

Then, the outlier data was identified based on Interquartile Range (IQR)= Q3-Q1; if a data was out of the range Q1-1.5 (IQR), Q3-1.5 (IQR), was identified as an outlier (20). Expert's views involving the outlier data were omitted. Then, to calculate the final weight of each risk factor, the remained views of experts were combined by Geometric Mean method. Prioritizing risk factors was performed according to the order of the calculated weights.
 
Ethical consideration
The study received ethics approval from the Ethical Committee of Mashhad University of Medical Sciences, Mashhad, Iran, and all participants consented orally.
 
Results
 
Based on studying the literature, the risk factors having a significant relationship with gestational diabetes in Iran following categorizing were: age above 30 years, number of previous pregnancies, obesity, family history of diabetes, history of previous unexplained perinatal loss or malformed infant birth, history of macrosomia infant birth, history of gestational diabetes or impaired glucose tolerance, glycosuria, history of infertility, hydraminus, history of caesarean in the previous and first childbirth. Among the 10 risk factors extracted from Up to Date, 8 risk factors were significant in Iran. For each of the 11 questionnaires returned by experts, paired comparisons matrix was created, normalized and its consistency ratio was calculated using formula 4 (Table IV). The responses related to DM4, DM5, greater than 0.1 and they were excluded from further calculations. For the remained 9 questionnaires, the weight of each index was calculated (Table V).
Based on table V, the view of DM1 about index C3 (0.26%), and the view of DM3 about C7 (14%) were identified as an outlier. Because of this, the views related to DM1 and DM3 were omitted completely and the rest of calculations were performed according to the views of the 7 remained experts. Based on the data of table V, the risk factor of ''history of gestational diabetes or impaired glucose tolerance in previous pregnancies'' has the highest weight from the perspective of 7 experts. These risk factors have also the highest weight difference with other risk factors. The final matrix resulted from combining the paired comparisons matrix of any expert has been shown in table VI. The final weight of each index is derived from this matrix. Matrix data shows that based on the consensus of experts, the risk factor of ''history of gestational diabetes or impaired glucose tolerance in the previous pregnancies" have a 7.26 fold importance than the index of ''maternal age >25 years''. Also, this risk factor has a 7.23 fold importance than ''history of previous unexplained perinatal loss or birth of malformed infants''.
The calculated weights and rank of each risk factors have been shown in table VII. The weight of each risk factor shows the rate of its effect on developing gestational diabetes. The risk factor of ''history of previous unexplained perinatal loss or birth of a malformed infant'', ''glycosuria at the first prenatal visit'', and ''maternal age >25 year'', by a trivial difference, have a least weight than other risk factors.

Table I. The 9-points scale used for the questionnaire of Analytical Hierarchy Process (17)


Table II. The derived risk factors for analysis


Table III. Random Index for various values of n (matrix dimension)


Table IV. Consistency Ratio of responses of each expert


Table V. Weight of each risk factor in each expert's view


Table VI. The combined matrix of paired comparisons matrix of each expert


Table VII. Calculated weights and ranking of risk factors for gestational diabetes 


Discussion
 
This research is conducted in order to determine the importance of risk factors for gestational diabetes in Iran by the Group AHP method. Among the risk factors derived based on studying the literature, the risk factor of ''history of gestational diabetes or impaired glucose tolerance in the previous pregnancies'' has the most importance in developing gestational diabetes than other risk factors. As the study by Huvinena showed, in spite of the healthier metabolic condition at first, non-obese women with the history of gestational diabetes had a higher rate of gestational diabetes outbreak (21). The healthcare providers should have a high sensitivity towards identifying the risk factors of gestational diabetes, especially the risk factor of the previous gestational diabetes (22). The experts' views in this study showed that glycosuria has a low importance in diagnosing gestational diabetes and the seventh rank among the eight risk factors. In the past, the test of glycosuria has had a weak sensitivity and characteristic. Recently, the guides of U.K. National Institute of Clinical Excellent have not recommended screening by this test (23).
In spite of many conducted studies, age was selected as a least important risk factor (24-26). In a systematic review and meta-analysis study by Jafari Shobeiri in 2015, the most important risk factors for gestational diabetes in Iran includes the history of gestational diabetes, history of family diabetes, BMI, the number of previous unexplained perinatal loss and number of the previous childbirth and history of having a macrosomic infant (3). Probably, changing lifestyle can be considered related to this result. In contrast, the study by Teh and coworkers by the method of logistic regression showed mother's age as the most important risk factor for gestational diabetes (27).
The study on 924 pregnant women that was conducted by Shirazian and coworkers in 2009 showed that the risk of complications of gestational diabetes rises with increase of age >30, BMI >30, and history of family diabetes (28). In the most of the studies conducted in Iran, the same screening method and diagnostic criterion were not used in all studies (25, 29-31), or the sample size has been low in some studies. In 17 provinces of Iran, a study of prevalence and identifying risk factors for gestational diabetes has not been performed; As a result, a precise statistics of prevalence and its risk factors in the whole country is not available (32). In this study, the risk factors derived from the literature were compared with the risk factors of Up To Date. The other risk factors were omitted because of the mentioned reasons.
The results of this study were obtained based on experts' views and AHP, and according to researchers' studies, it seems that it is the first study on this topic. In most studies, the importance of risk factors has been determined by regression. AHP has been widely used in the healthcare sector (18). For example, prioritizing risk factors of obesity and risk factors of Obstructive Sleep Apnea, the study by Pecchia and coworkers to derive users' s demands in CT (Computed Tomography) using the views of 5 experts, the study by Danner and coworkers based on the views of 7 experts and 12 patients aiming at eliciting patients' preferences for assessing health technologies, the study by Hilgerink using the views of 7 experts to assess the added value of the Twente Photo acoustic Mammoscope in breast cancer diagnosis, and the study by Suner for decision support in rectal cancer using the views of 5 experts can be referred to (33-38).
The required sample size is one of the discussions related to the AHP method. There is no subtle rule about calculation the sample size, but consensus and common agreement is that it does not need to large sample size (39). In this study, the questionnaires were distributed among all the research population and finally, 11 people responded. In AHP method, properly selecting the experts in the field of research is much more important than the number of them (39). The participants in this research were all Endocrinology Experts with a mean of 8.8 years of work experience, were in a close contact with the mothers suffered from gestational diabetes, and this causes more recognition of risk factors related to this disease and enhancement of results.
The available limitation in conducting research is that only the views of Endocrinology Experts of Mashhad province are considered. Race and ethnicity as a risk factor have been stated in the valid scientific references, but so far no study has addressed the effect of this risk factor in gestational diabetes in Iran. However, because Mashhad is one of the metropolises of Iran in which peoples of other provinces live, this limitation cannot influence on the generalizability of the research results definitely.
 
Conclusion
 
Conducting a comprehensive study for examining the prevalence and identifying risk factors for gestational diabetes in Iran seems necessary. According to this fact that various ethnicities live in Iran, studying the difference of prevalence and risk factors among them is interesting. Given the board applications that the AHP has in the healthcare sector, using the results of this study by the physicians as criteria for identifying the pregnant women at risk and applying diagnostic methods is recommended. Also, to prevent gestational diabetes, the healthcare sector can consider these priorities determined in experts' views.
 
Acknowledgments
 
We would like to thank all of the endocrinologists for their participations in this study. This study was supported by a grant from Mashhad University of Medical Sciences, Mashhad, Iran.
 
Conflict of interest
 
The authors declare that there is no conflict of interests regarding the publication of this paper.

 
Type of Study: Original Article |

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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.
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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.
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