https://imcjms.com Ibrahim Medical College Journal of Medical Science https://imcjms.com/registration/journal_full_text/60 Tue, 02 Aug 2016 11:41:03 +0000 Ibrahim Med. Coll. J. 2013; 7(2): 21-27 Background For Bangladesh, it seems important to determine the prevalence of GDM for several reasons. Firstly, Bangladeshi women showed higher prevalence of IGT than their male counterpart.7 Secondly, compared with the other Southeast Asian Region (SEAR), Bangladesh is known to have higher birth rate and higher prevalence of multiparous women.8 It is also reported that multiparity contributes to the development of glucose intolerance.9 Thirdly, the prevalence of infant mortality is also high in Bangladesh.8 Fourthly, high prevalence of cardiovascular morbidity and mortality in the SEAR may be due to higher risk among the offspring of mother with gestational diabetes.10 Finally, though not documented, frequency of congenital malformations and low birth weight and fetal loss appears to be higher in Bangladesh. Considering the above-mentioned factors one can postulate the importance of assessing the prevalence of GDM in the population. A single study was carried out, which reported a high prevalence of GDM (6.8%).14 However, there has been no follow-up report and outcome of these GDM subjects. This study addressed to determine the prevalence of GDM and determine the outcomes of these pregnancies like fetal loss, congenital anomalies, perinatal morbidity and mortality. Research design and methodology This population-based prospective cohort of pregnant women was selected from the rural communities of ten villages having most typical rural characteristics. The rural people of the study area maintain traditional lifestyle. The characteristics of rural life defined for this study are the livelihood primarily related to agrarian activities (ploughing, plantation, irrigation, harvesting, fisheries, poultry etc.). The rural women are actively involved in these agricultural physical works. Sample size determination The study was conducted in purposively selected ten villages with a total population of 22000 in Nandail under the district of Mymensingh. According to Bangladesh Bureau of Statistics there were 150 eligible couple (married women of age 15-45y) per 1000 population in Bangladesh [BBS].15 Thus, 3300 eligible participants were expected in a population of 22000. This estimation was based on the prevalence rate of pregnancy (5 per thousand women) through personal communication from an ongoing “JivitA project” in Rangpur, where 65000 married women of reproductive age have been followed up since 2001. Additionally, we considered the prevalence of diabetes (T2DM), impaired fasting glucose (IFG) and gestational diabetes (GDM) were 4.0%, 13.0% and 6.8% in the rural population.14,16 Considering all these data we estimated at least 125 subjects could have been detected as diabetes with pregnancy and GDM. The stepwise selections of the pregnant women are depicted in Figure 1. Data collection     The diagnosis of pregnancy was made on the basis of clinical findings: (i) a history of amenorrhoea, (ii) an enlarging uterus, (iii) nausea or vomiting, (iv) breast tenderness, (v) Montgomery’s tubercles, (vi) quickening, and (vii) other signs, e.g. fundal height, chloasma, linea nigra, striae, fetal heart sound, palpation of fetus.17 All these above mentioned variables (biophysical characteristics) were compared between pregnant and non-pregnant women. For the pregnant group, the comparisons were made between GDM and non-GDM.   We used diagnostic criteria of gestational diabetes mellitus (GDM) revised by American Diabetes Association Diabetes (ADA, 2013).18,19 According to ADA criteria OGTT is recommended noting Data analysis – The prevalence rates of GDM are shown in simple percentages and presented with 95% confidence interval (CI). The biophysical characteristics are given in mean with standard deviation SD). The Chi-sq tests were used to determine the association between hyperglycemia and pregnancy and outcomes. Results The prevalence of pregnancy was found 9.3, 76.1 and 14.7% in the age groups <19, 20-34 and >35y, respectively. The comparisons of anthropometric and biochemical characteristics between pregnant and non-pregnant women were shown in table 2. As expected, anthropometric variables (BMI, WHR) were significantly higher in the pregnant women than their non-pregnant counterparts (p<0.001). In contrast, both systolic and diastolic blood pressure was found significantly lower in the pregnant women (p<0.001). Interestingly, there was no significant difference of fasting plasma glucose between them though the prevalence (95% CI) of hyperglycemia (FPG >5.1mmol/l) was found significantly higher in the non-pregnant than the pregnant women [19.8% (18.9 – 20.8) vs. 8.9% (7.0 – 10.8)].   Table-1: Distribution of census population by age, sex and marital status     Table-3: Comparison of characteristics between pregnant women with and without GDM (FPG >5.1 vs. FPG <=5.1 mmol/l).     Undoubtedly, this pregnancy cohort in a rural setting is a unique study. It has been a common impression that prevalence of hyperglycemia was more in the gestational women. There are reports that hyperglycemia in pregnancy are detrimental to pregnancy outcomes.4-6 This pregnancy cohort showed that the pregnant women had lower FPG and significantly lower prevalence of hyperglycemia. In addition, contrary to the other findings suggesting unfavorable outcomes in GDM, this study observed no significant adverse outcome among the GDM subjects compared with the non-GDM subjects. It is not clear why there was no excess morbidity or mortality in the GDM women. This may due to inadequate number in the GDM group for comparison as against a larger number of the non-GDM women (20 vs. 204). May be there are some other factors that remain to be identified. The study experienced some limitations. We could investigate only once for history, anthropometry and collection of blood sample for screening of fasting plasma glucose and lipids. The interim pregnancy period could not be monitored for glycemic fluctuations if any. A single screening test for GDM may not reflect the entire period of metabolic status in pregnancy. Thus, there might be some errors in assessing the metabolic status related to pregnancy outcomes. Further study may be undertaken considering such weakness that we experienced in this study. Had we got the facility for assessing HbA1c or monitoring plasma glucose in subsequent months we could have better conclusions. Conclusions   1.   American Diabetes Association: Gestational diabetes mellitus (Position Statement). Diabetes Care 2000; 23:(Suppl.1): S77-S79. 3.   T Wagaarachchi L, Fernando P, Premachadra DJS, Fernando P. Screening based on risk factors for gestational diabetes in an Asian population. J Obstet Gynaecol 2001; 21: 32-34. 5.   Farrell T, Neale L, Cundy T. Congenital anomalies in the offspring of women with type 1, type 2 and gestational diabetes. Diabet Med 2002; 19: 322-6. 7.   Sayeed MA, Hussain MZ, Banu A, Ali L, Rumi MAK, Azad Khan AK. Effect of socioeconomic risk factor on difference between rural and urban in the prevalence of diabetes in Bangladesh. Diabetes Care 1997; 20: 551-555. 9.   Juntunen K, Kirkinen P, Kauppila A. The clinical outcome in pregnancies of grand multiparous women. Acta Obstet Gynecol Scand 1997; 76(8): 755-9. 11.Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, Robinson JS. Australian Carbohydrate Intolerance Study in Pregnant Women (ACHOIS) Trial Group. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med 2005; 352: 2477-86. 13.Most OL, Kim JH, Arslan AA, Klauser C. Maternal and neonatal outcomes in early glucose tolerance testing in an obstetric population in New York city. J Perinat Med 2009; 37(2): 114-7. 15.Bangladesh Bureau of Statistics. Statistical Pocket Book of Bangladesh 2005. Ed: Chowdhury JA, Dey AK, Sikder AR, Statistical Division, Ministry of Planning, Government of The People’s Republic of Bangladesh. 17.Bovonne S, Pernoll ML. Normal pregnancy and prenatal care. In: Decherney AH and Nathan L, eds. Current Obstetric and Gynecologic Diagnosis and Treatment, 9th edn. XXX: McGraw-Hill 2003: 193-198. 19.Carpenter MW, Coustan DR. Criteria for screening test for gestational diabetes. Am J Obstet Gynecol 1982; 144: 768-773. 21.Currie LM, Woolcott CG, Fell DB, Armson BA, Dodds L. The Association Between Physical Activity and Maternal and Neonatal Outcomes: A Prospective Cohort. Matern Child Health J 2013. 23.Yang YD, Zhai GR, Yang HX. Factors relevant to newborn birth weight in pregnancy complicated with abnormal glucose metabolism. Zhonghua Fu Chan Ke Za Zhi 2010; 45(9): 646-51 (chinese). 25.Sugiyama T, Metoki H, Hamada H, Nishigori H, Saito M, Yaegashi N, Kusaka H, Kawano R, Ichihara K, Yasuhi I, Hiramatsu Y, Sagawa N. The Japan Gestational Diabetes Study Group. A retrospective multi-institutional study of treatment for mild gestational diabetes in Japan. Diabetes Res Clin Pract 2014; pii: S0168-8227(13) 00450-6. 26.  Freathy RM, Hayes MG, Urbanek M, Lowe LP, Lee H, Ackerman C, Frayling TM, Cox NJ, Dunger DB, Dyer AR, Hattersley AT, Metzger BE, Lowe WL, Jr. HAPO Study Cooperative Research Group. Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study: common genetic variants in GCK and TCF7L2 are associated with fasting and post-challenge glucose levels in pregnancy and with the new consensus definition of gestational diabetes mellitus from the International Association of Diabetes and Pregnancy Study Groups. Diabetes 2010; 59: 2682–89. [PubMed] 2026 Ibrahim Medical College. All rights reserved.