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Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh

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Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh
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  Sep. 2010, Volume 7, No. 9 (Serial No. 70) Journal of US-China Medical Science, ISSN 1548-6648, USA  Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh Syed Muhammad Baqui Billah 1 , Muna shalima Jahan 2 , Bounelome Keobouahome 1 , Takaaki Kinoue 1 , Yoshihisa Watanabe 1  and Tetsu Watanabe 1   1. Tokai University Graduate School of Medicine, Isehara, Kanagawa 259-1193, Japan 2. Shaheed Suhrawardi Medical College, Dhaka 1207, Bangladesh Abstract:   Objective : To assess socio-epidemiology of Antepartum Fetal Death (AFD) in Bangladesh. Method : Fifty three pregnant women with intra-uterine fetal death before or after delivery were interviewed in gynecology in-patient of Dhaka Medical College Hospital during 2005-2008. Selected socio-demographic factors like age, education, occupation, income etc. and epidemiologic factors like previous stillbirth or congenital anomaly history, antenatal history, and other medical conditions like gestational diabetes and hypertension, urinary tract infection, exposure to trauma, drug or radiation were sought. One hundred and ten mothers with live  pregnancy (NAFD) were also interviewed as control. Results : Both groups of respondents were young. AFD mothers were married at an earlier age (0.04), got pregnant earlier (p=0.05), were less educated (p<0.001) as were their husbands (p=0.001), fell into heavy working group (p=0.01) and had lower family income (p<0.001) compared to controls. History of stillbirth (p=0.02) and congenital anomaly (0.001) in previous pregnancy were associated significantly with AFD. Less antenatal care (ANC), antepartum bleeding, gestational diabetes and hypertension, urinary tract infection, fever were significantly associated with AFD group while history of trauma, taking any risky drug or radiation exposure were not associated. On logistic regression adjusted for socio-demographic variables, increased ANC visit appeared protective (OR=0.017, 95%CI=0.003-0.09) whilst history of stillbirth (OR=5.59, 95%CI=1.21-25.79), pregnancy induced hypertension (OR=7.87, 95%CI=1.79-34.62) were significant predictors with gestational diabetes (OR=12.56, 95%CI=0.85-185.08) being just insignificant. Reversely the model adjusted the epidemiologic factors to found only higher family income (OR: for middle income family=0.21, 95%CI=0.06-0.77 and for high income family=0.30, 95%CI=0.08-1.03) as good predictors of AFD. ANC came out to be the most significant predictive variable to reduce AFD nearly 100%.  Conclusion : Increasing the age at marriage and pregnancy, education, adequate rest during pregnancy and off course, increasing coverage of ANC could bring about satisfactory outcome if taken care of before future pregnancies. Key words:  Antepartum Fetal Death (AFD), socio-epidemiology, epidemiology, Bangladesh. 1. Introduction   Any pregnancy can face life threatening complications during its course. So it is important to follow every pregnancy with caution as the complications might lead to maternal as well as fetal death [1]. Developed countries achieved marked reduction in maternal and infant mortality and now are focusing on perinatal mortality [2-4]. While developed countries intervened into the matter to reduce its incidence [5-8] searching through the causes, the Corresponding author : Syed Muhammad Baqui Billah, PhD candidate, research fields: reproductive health, health, systems research. E-mail: sbbillah@gmail.com. situation was never satisfactory in developing countries [9, 10]. Among the different causes related to AFD, socio-epidemiologic factors like mother’s age, race, inadequate ante natal care (ANC), social burden,  pregnancy decision, education, parity, previous stillbirth have been identified to be most frequently associated with the risk of AFD [11-21]. Pregnancy induced hypertension (PIH), antepartum hemorrhage (APH), gestational diabetes mellitus (GDM), infection, non-cephalic presentation, small for gestation etc. had  been identified as important maternal factors. Congenital malformations and Rh iso-immunizations were important fetal [13, 18, 19] factors.  Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh 12 Information regarding the glitch had never been adequate in Bangladesh as most of the researches were addressing perinatal [22-25] mortality. So, we needed a preliminary idea on it. The objective of the study was to assess the relationship of the socio-demographic and epidemiologic risk factors of AFD. The primary null hypothesis was that there is no difference of socio-demographic or epidemiologic factors of mothers with AFD or no AFD (NAFD). 2. Material and Methods 2.1 Subject Selection and Data Collection The case control study investigated mothers with intra-uterine death before and/or after delivery, without any debilitating illness and willing to participate, in Dhaka Medical College Hospital (DMCH) during the  period of 2005-2008 with pre-tested semi-structured questionnaire. Permission for this study was obtained from Bangladesh Medical Research Council (BMRC). Stillbirth was defined in this study as any fetal delivery after 28 weeks of gestation showing no signs of life. If the death occurs before the onset of labor, it is called Antepartum Fetal Death (AFD). For every patient with AFD, 1 mother with normal delivery was initially decided to be interviewed following same protocol. As there was no good record keeping system in Dhaka Medical College Hospital, the researchers decided to interview the cases they encountered during the study period and to increase the number of controls to 2 per case. In turn, 53 AFD and 110 NAFD mothers could be covered during study  period. Patients’ background information like age, education, occupation, parity, age at marriage and at first pregnancy, monthly family income, and husband’s education were recorded. Antenatal (ANC) history and number of ANC checkups in current pregnancy, average working hour and history of previous stillbirth and congenital malformation were sought. Present  pregnancy complains of gestational diabetes mellitus (GDM), pregnancy induced hypertension (PIH), fever and urinary tract infection (UTI) in 3rd trimester and antepartum hemorrhage (APH) were also asked. 2.2 Data Analysis The collected data were cleaned and checked before final entry to SPSS. The age was categorized starting with <20 years and then into a 5 years interval group finally ending at ≥ 30 years. The age at marriage and first pregnancy were classified into two dividing by ≤ 20 years. The gestational age was categorized as  premature if gestational age was ≤ 38 years. The monthly income was categorized 5000 taka, ≥ 5000~<10000 taka, and >10000 taka (1 Bangladesh Taka = 0.7 US Dollar) a month. Literacy below secondary school was categorized as low education; secondary to higher secondary was considered some education and above was recorded as good education. Housewives working ≥ 8 hours/day during the latest  pregnancy were considered heavy working mothers including daily laborers and garments workers while those working < 8hours/day including teachers, service holders or craftswomen were considered sedentary mothers. Background factors were compared between AFD and NAFD cases. Continuous variables were assessed with Mann-Whitney U test and categorical values were assessed by 2 test. A p value of <0.05 was considered significant. Continuous variables were presented as means and standard deviations and categorical variables were presented as  proportions. After assessing the basic characteristics, univariate analysis was done with the epidemiologic history of pregnancy related information. The significant background variables were gathered together for predicted probability to create propensity score. This propensity score was adjusted in logistic regression and the significant variables from univariate analysis were put into the logistic model one by one. The variables came out significant through this process were put together into one model after adjusting for propensity score to assess the  predictive variables causing AFD. In the same way,  Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh 13 the significant epidemiologic factors were gathered together to create propensity score and were adjusted to assess the effect of socio-demographic variables on AFD. 3. Results Table 1 describes the baseline characteristics of both AFD and NAFD groups. Both groups were above 25 years on average, mostly 20-24 years (38.0%) ranging  between 16-38 years. AFD mothers were married at average 18.51±2.8 years, significantly earlier (p=0.04) than NAFD mothers (19.64±3.81). The age at first  pregnancy were also significantly different (p=0.009) in AFD than NAFD mothers. The average monthly family income of AFD group was 5676±4674 taka, significantly lower (p<0.001) than the 11093±9176 taka of NAFD group. The median income of AFD group was 3500 taka, more than half (54.72) of them earned <5000 taka a month ranging from 500 taka to 20000 taka. The median income of NAFD group was 8000 taka, while nearly half (47.27%) NAFD mothers’ monthly income was ≥ 10000 taka, the lowest being 0 Table 1 Characteristics of respondents 1 . Variables 2  No AFD (n=110) AFD (n=53) p 3  Age 25.71 ±5.0 25.15 ±6.45 0.27 Age at marriage 19.64±3.81 18.51±2.85 0.04 Age at first pregnancy 21.72±3.94 20.13±3.08 0.009 Clinical gestational age 39.22±1.34 35.19±3.62 <0.001 Monthly income 11093.64±9176.27 5676.42±4674.24 <0.001 Age group <20 9 (8.18) 9 (16.98) 0.08 20-24 41 (37.27) 21 (39.62) 25-29 29 (26.37) 6 (11.32) ≥ 30 31 (28.18) 17 (32.08) Education Illiterate 7 (6.36) 15 (28.30) <0.001 Low Education 59 (53.64) 30 (56.30) Good Education 44 (40.00) 8 (15.10) Husbands’ Education Illiterate 6 (5.45) 10 (18.87) 0.001 Low Education 43 (39.10) 28 (52.83) Good Education 61 (55.45) 15 (28.30) Occupation Sedentary 65 (59.09) 20 (37.74) 0.01 Heavy 45 (40.01) 33 (62.26) Income group < 5000 12 (10.91) 29 (54.72) <0.001 5001-9999 46 (41.82) 14 (26.41) ≥  10000 52 (47.27) 10 (18.87) 1 Continuous values are presented in means and standard deviations, categorical values in proportions. 2 Age, age at marriage and age at first pregnancy in completed years, clinical gestational age and First ANC time in weeks of gestation, monthly income in Bangladesh Taka (BDT: 1 BDT=1/70USD) 3  p  values for continuous variables are based on the nonparametric Mann-Whitney U test while those for categorical variables are  based on chi-square test.  Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh 14 Table 2 Univariate comparison of pregnancy history 1 .  No AFD (N = 110) AFD (N = 53) p Working hour/day 8.46±2.69 9.89±2.13 0.001 First ANC time 12.99±6.40 15.54±6.28 0.08 Total number of ANC 6.63±3.26 3.42±1.38 <0.001 Gravid 0.71 Primigravid 61 (55.50) 31 (58.49) Multigravid 49 (44.50) 22 (41.51) Previous History Stillbirth 0.02  No 106 (96.36) 46 (86.79) Yes 4 (3.64) 7 (13.21) Congenital anomaly 0.001  No 110 (100) 48 (90.57) Yes 0 5 (9.43) Present Pregnancy Complains 2  GDM 0.07  No 109 (99.09) 50 (94.34) Yes 1 (0.91) 3 (5.66) PIH 0.009  No 106 (96.36) 45 (84.91) Yes 4 (3.64) 8 (15.09) ANC <0.001  No 2 (1.82) 29 (54.72) Yes 108 (98.18) 24 (45.18) Bleeding 0.02  No 100 (90.91) 41 (77.36) Yes 10 (9.09) 12 (22.64) Fever 0.06  No 99 (90.0) 42 (79.25) Yes 11 (10) 11 (20.75) UTI 0.003  No 104 (94.55) 42 (79.25) Yes 6 (5.45) 11 (20.75) Trauma 0.16  No 107 (97.27) 49 (92.45) Yes 3 (2.73) 4 (7.55) Diarrhoea/dysentery 0.43  No 105 (95.45) 49 (92.45) Yes 5 (4.55) 4 (7.55) Radiation Exposure  No 110 53 Yes 0 0 Taking any teratogenic drug 0.32  No 108 53 Yes 2 0 1 Continuous values are presented in means and standard deviations, categorical values in proportions. 2 GDM, PIH, Bleeding history in 2nd/3rd trimester; fever, UTI, trauma, diarrhea/dysentery in 3rd trimester; radiation history, taking any tetarotegnic drug in 1st trimester  Socio-Epidemiology of Antepartum Fetal Death in Tertiary Hospital in Bangladesh 15   taka of some unemployed families, while the highest was 60000 taka, depicting the skewed income of both groups. Majority of AFD mothers were low educated followed by illiterate, significantly different (p<0.001) from NAFD mothers who mostly had low followed by good education. Similar education profile was observed in husbands’ education between two groups. Most AFD mothers (62.26%) were heavy workers whereas NAFD mothers (59.09%) were mainly sedentary workers & this finding was statistically significant (p=0.01).   The univariate analysis in Table 2 depicts the epidemiology of pregnancy related information. It shows that AFD mothers worked nearly 10 hours/day on average during the current pregnancy, which was significantly higher (p=0.001) than average 8.5 hours working by NAFD mothers. The first ANC visit of AFD mothers were around 16 weeks of their gestation on average, around 3 weeks later than that of NAFD mothers and was statistically significant (p<0.001). In the same manner total number of ANC visit by AFD mothers was nearly half compared to NAFD mothers’ total ANC visit. In both the groups the mothers were mainly primigravid. Thirteen percent of AFD mothers gave history of stillbirth in their previous pregnancies while it was only 3.64% for NAFD mothers (p=0.02). Five AFD mothers gave history of congenital anomaly in their previous pregnancies while there was none such in NAFD group (p=0.001). Eight (15.09%) AFD mothers suffered from PIH, significantly higher (p=0.009) than 4 (3.64%) NAFD mothers with PIH. The association of GDM and AFD was not so significant (0.07). Also there were statistically significant association of ANC, bleeding, fever and UTI with AFD but no such association of trauma, diarrhea, radiation exposure or taking any teratogenic drug was found. After adjusting the background variables together, from propensity score, in logistic regression analysis, risk factors were assessed one by one to see the effect on AFD. History of previous stillbirth (p=0.02), PIH (0.009), ANC (<0.001) and UTI (0.03) became risk factors and GDM was just significant (0.07). Fever (0.13), bleeding (0.13) and working hour (0.54) were not significant. Utilizing our clinical knowledge we wanted to put GDM in our model. Putting GDM together with other significant variables into one model, we found that UTI was not significant and GDM remained as just significant. Finally 4 variables were adjusted with background propensity score to find ANC (OR: 0.017; 95%CI=0.003-0.09) as very significant risk factors with PIH (OR: 7.87; 95%CI=1.79-34.62) and stillbirth (OR: 5.59; 95%CI=1.21-25.79) though GDM (Adjusted OR: 12.56; 95%CI=0.85-185.08) was just significant (Table 3). It was observed that ANC solely can reduce nearly 100% of AFD irrespective of other epidemiological or socio-demographic risk factors. In the same manner we tried to look at the socio-demographic variables after adjusting the significant epidemiologic factors through the way of  propensity score to check the effect of socio-demographic factors on AFD. The analysis revealed only higher family income (OR: middle Table 3 Multivariable analysis of factors predictive of AFD. Epidemiologic Adjusted Odds Ratio 95% CI p Stillbirth 5.59 1.21-25.79 0.03 ANC 0.017 0.003-0.09 <0.001 PIH 7.87 1.79-34.62 0.006 GDM 12.56 0.85-185.08 0.065 Socio-demographic Income ( ≥ 5000 - <10000 taka) 0.21 0.06-0.77 0.02 Income ( ≥ 10000 taka) 0.30 0.08-1.03 0.06
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