Public Health of Indonesia Herman. , et al. Public Health of Indonesia. 2018 December. :146-153 http://stikbar. org/ycabpublisher/index. php/PHI/index ISSN: 2477-1570 Original Research DIFFERENCES OF MATERNAL SOCIODEMOGRAPHIC CHARACTERISTICS WITH SPONTANEOUS PRETERM BIRTH AMONG HOSPITALS IN INDONESIA: A COMPARATIVE STUDY Sriyana Herman1. Budi Santoso2*. Hermanto Tri Djoewono3 Department of Reproductive Health. Fellow of Ph. D Program. Medical Faculty. Universitas Airlangga. Surabaya. Indonesia Faculty of Medicine. Dr. Soetomo Teaching Hospital. Universitas Airlangga. Surabaya. Indonesia Received: 4 October 2018 | Revised: 30 October 2018 | Accepted: 3 December 2018 *Correspondence: Budi Santoso Faculty of Medicine. Dr. Soetomo Teaching Hospital Universitas Airlangga. Surabaya. Indonesia E-mail: budi. santoso@fk. Copyright: A the author. YCAB publisher and Public Health of Indonesia. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT Background: Maternal sociodemographic characteristics can be used to prevent preterm birth. Objective: To identify differences in maternal sociodemographic characteristics with spontaneous preterm birth among hospitals in East Java. Indonesia. Methods: This was a descriptive study with comparative design in 134 mothers who experienced preterm birth at eight Data were analyzed using Independent samples t-test. Result: Sixteen variables were significantly different in maternal sociodemographic characteristics with spontaneous preterm birth among eight hospitals, namely: gestational age (CI 95%:10. 02, p <0. , maternal age (CI 95%:0. 03, p <0. , smoking (CI 95%:9. 01 p <0. Edinburgh Postnatal Distress Scale (EPDS) (CI 95%:6. p <0. , the fetus mobile (CI 95%:2. 58, p <0. , the number of visits during pregnancy (CI 95%:5. 36, p <0. , history of premature (CI 95%:7. 73, p <0. , history of disease (CI 95%:9. 97, p <0. , history of abortion (CI 95%:9. 65, p <0. , height (CI 95%:9. 83, p <0. BMI (CI 95%:0. 74, p <0. Mid Upper Arm Circumference (MUAC) (CI 95%:2. 96, p <0. , periodontal infection by (CI 95%:6. 45, p <0. , bleeding in young and old pregnancy (CI 95%:7. 28, p <0. , anemia status (CI 95%:2. 19, p <0. and BV status (CI95%:9. 45, p <0. Conclusion: There were significant disparities in maternal sociodemographic characteristics with preterm birth among Our findings can be used as the basic data for future research in an effort to prevent premature birth disorders based on maternal sociodemographic characteristic. Keywords: sociodemographic characteristics, hospitals, preterm birth. Indonesia BACKGROUND Preterm birth is influenced by many of risk Robinson and Nortwitz . collected several sociodemographic risk factors from several theories, including absence of partner, low socioeconomic, anxiety and stress, depression . ife problems such as divorce, separation, deat. , ever Ketosis-Prone Diabetes, history of secondtrimester abortion, history of cervical surgery. Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 short length of the cervix. STI, infectious disease, bacteriuria, periodontal disease, placenta previa, placental abruption, vaginal bleeding , previous history of preterm birth, drug abuse, smoking, maternal age. AfricanAmerican race, low BMI nutrition, inadequate prenatal care, anemia, excessive uterine contractions, low education level, fetal environmental factors . heat and air According to Cunningham et al. , the highest risk of preterm birth is a history of previous birth itself. Sample The samples were all mothers after preterm birth recorded in medical records at 8 hospitals, i. Soewandhi hospital. Universitas Airlangga hospital. Islam Jemur Sari hospital. Sidoarjo hospital. Madiun Sogaten hospital. Jombang hospital. Ibnu Sina Gresik hospital, and Ngawi hospital. The inclusion criteria were spontaneously preterm birth mothers 6 hours-3 days, spontaneous single pregnancy without complications, could communicate well, and have a health record book. The exclusion criteria were all deliveries with complications or abnormalities such as hypertension in pregnancy, pregnancy with diabetes mellitus, multiple pregnancies, hydramnios, antepartum bleeding, uterine anatomic abnormalities, pregnancy with tumors, and congenital abnormalities of the Preterm classification according to gestational age were between 20-37 weeks, earlier preterm birth between 20-23 weeks, early preterm birth between 24-33 weeks, and late preterm birth between 34-36 weeks (Berghella, 2. While according to WHO . birth that occurs between 28 weeks gestation to less than 37 weeks . calculated from the first day of the last menstrual period in the 28-day cycle. Preterm birth is still a problem in the world including Indonesia. Related to the prevalence, perinatal morbidity and mortality are the main causes of infant mortality and the second cause of death after pneumonia in children under five years old (Erez, 2. The incidence of preterm birth is different in each country, in Europe the figure was 5-11%, while in the USA was In developing countries the number of occurrences is still much higher, for example in Sudan around 31%. India 30%, and South Africa 15% (Osterman et al. , 2. , while Indonesia ranks 5th largest from 184 countries in 2010 (WHO, 2010 in Purisch and Cynthia. More than one million babies die of preterm birth every year in the world or 1 baby every 30 seconds (Berghella, 2. Instrument The sociodemographic instrument was developed by the researchers for data collection, including gestational age, motherAos age, education, occupation, number of children, parity, distance of pregnancy, weightlifting work, smoking. EPDS, fetus mobile, sleeping time, number of visits during pregnancy, history of preterm birth, history of disease, second-trimester abortion history, social economy, previous childAos sex, body weight (BW), body mass index (BMI), upper arm circumference, periodontal infection, bleeding in young and old pregnancy, anemia status, status of bacterial vaginosis (BV). Statistical analysis Data were analyzed using independent T-test to compare the differences in maternal (Sastroasmoro and Ismail, 2. Ethical consideration This study has been approved by the Medical Faculty of Medicine of of Airlangga University. The researchers assured that all participants have obtained appropriate informed consents. METHODS Study design This was a descriptive study with comparative This study was conducted from November 2017 to July 2018 in 8 hospitals in East Java. Indonesia. Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 RESULTS 4%). Airlangga Hospital with 25 respondents . 7%). Gresik. Jombang and Ngawi Hospital with 12 respondents respectively . 0%). Sidoarjo Hospital with 24 respondents . 9%), and Madiun Hospital with 10 respondents . 5%) (See Table . ParticipantsAo characteristics The number of respondents was 134 mothers with spontaneous preterm birth in 8 hospitals Jemur Sari Hospital with 25 respondents . 7%). Soewandhi Hospital with 14 Table 1 Percentage of maternal sociodemographic characteristics with preterm birth among hospitals Sociodemographic Gestational age 24-33 weeks 34-36 weeks MotherAos age 20-35 weeks <20/>35 weeks Education >Senior High School 2 people Parity Multipara Primipara Pregnancy Distance <2 years >2 years Weightlifting work <5 hr/day >5 hr/day Smoking Yes EPDS Mild/Medium . core 0-. Heavy: score >13 Fetus mobile Mobile>4x/half an hour Less mobile <4x/half an Sleeping time 7-8 hour/day <7/>9 hour/day Number of visits during >4 times <4 times History of preterm birth Never 1-2/>2 times History of disease None Yes Hospital n (%) Hospital n (%) Hospital n (%) Hospita n (%) Hospital n (%) Hospital n (%) Hospital n (%) Hospital n (%) 5 . Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 Second-trimester abortion None 1-2/>2 times Social economy >Rp. 145 cm <145 cm Body Mass Index (BMI) 18,5-25 Kg/m2 <18,5/>35 Kg/m2 Upper arm circumference >23. 5 cm <23. 5 cm Periodontal infection None Yes Bleeding in young and old None Yes Anemia status Hb normal: 10. 5-11 g/dl Hb abnormal: <10. 5 g/dl Status Bacterial vaginosis (BV) Not inspected Positive 24 . Remarks: 1: Jemur Sari Hospital, 2: Soewandhi Hospital, 3: Airlangga Hospital, 4: Gresik Hospital, 5: Sidoarjo Hospital, 6: Jombang Hospital, 7: Madiun Hospital, 8: Ngawi Hospital Differences in maternal sociodemographic characteristics with preterm birth among of visits during pregnancy . <0. , history of preterm . <0. , history of disease . <0. , history of abortion . <0. , height . <0. BMI . <0. , upper arms circumference . <0. , periodontal infection . <0. , bleeding young/old pregnancy . <0. , anemia status . <0. , and BV status . <0. ee Table Our analysis showed that, out of 25 variables, only 16 significant variables had significant gestational age . <0. , maternal age . <0. , smoking . <0. EPDS . <0. , fetal immovable . <0. , number Table 2 Analysis of differences in maternal sociodemographic characteristics with preterm birth among hospitals Sociodemographic characteristics Gestational age MotherAos age Education Occupation Number of Child Parity Pregnancy period Weightlifting work Mean difference Group 1 Group 2 95% CI of the difference Lower Upper Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 P value* Smoking EPDS Fetal movements The amount of sleep Number of visits during pregnancy History of premature birth History of Mother's Sickness History of Abortion Social economy ChildAos sex Height BMI Upper arms circumference (MUAC) Periodontal infection Bleeding Anemia BV Status *Analysis used by independent sample T test DISCUSSIONS who did not have a smoking habit have an average of 15 mothers per hospital, with the highest number in Sidoarjo Hospital by 24 mothers . 9%) and mothers who had smoking habits had an average of 1 mother per hospital, with the highest number in Jemur Sari Hospital and Gresik Hospital by 4 mothers respectively . 0%). According to Baron et al. , . that mothers who consumed cigarettes Ou10 cigarettes per day were associated with preterm birth (OR 2. CI 95% 1. compared to mothers who consumed cigarettes O10 cigarettes per day (OR 1. 95% CI 0. Whereas according to Sentilhes et al. , . that among preventable risk factors of spontaneous prematurity, only cessation of smoking is associated with decreased prematurity. Findings showed that only 16 variables had significant differences in sociademographic Our discussion is described in each variable. Gestational age, indicated that the average gestational age of preterm birth was significantly different among hospitals, as the age of early preterm birth . -33 week. has an average of 5 mothers in every hospital. The highest number in Sidoarjo Hospital by 10 mothers . 4%) and late preterm birth . -36 week. has an average of 11 mothers per hospital with the highest number in Airlangga Hospital by 22 mothers . 4%). Maternal age, indicated that the average age of preterm birth was significantly different between hospitals. Maternal age at 20-35 years has an average of 11 mothers per hospital, with the largest number at the Jemur Sari Hospital by 22 mothers . 4%) and maternal age <20 /> 35 years had an average of 5 mothers per hospital, with the highest number in Airlangga Hospital by 9 mothers . 7%). According to Fuchs et al. , . that maternal age . years and ove. was associated with preterm birth and a maternal age of 30A34 years was associated with the lowest risk of EPDS, indicated that the average preterm birth of EPDS was significantly different between hospitals, i. , mothers who have mild and moderate EPDS . core 0-. have an average of 14 mothers per hospital, with the highest number at Jemur Sari Hospital by 22 mothers . 4%) and mothers who had severe EPDS . core> . had an average of 2 mothers per hospital, with the highest number found in Soewandhi Hospital by 6 mothers . , 5%). Rallis et al. , . said that higher depression scores in early pregnancy were proven to predict anxiety and higher stress values in late According to Baron et al. , . mothers who consumed cigarettes Ou10 Smoking, indicated that the average smoking habit of preterm birth was significantly different between hospitals, namely mothers Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 cigarettes per day were associated with preterm birth (OR 2. CI 95% 1. compared to mothers who consumed cigarettes O10 cigarettes per day (OR 1. 95% CI 0. History of disease, indicated that the average history of preterm birth was significantly different between hospitals, i. , mothers who did not have a history of disease had an average of 15 mothers per hospital, with the highest number in Jemur Sari Hospital by 23 mothers . 2 %) and mothers who have a history of disease have an average of 1 mother per hospital, with the highest number in Sidoarjo Hospital by 3 mothers . 72%). Fetal movement, indicated that the average movement of the fetus preterm birth was significantly different between hospitals, i. mothers who have fetal movements >4x/half hour had an average of 14 mothers per hospital, with the highest number in Airlangga Hospital by 20 mothers . 9%) and mothers who have fetal movements <4x/half hour have an average of 2 mothers per hospital, with the largest number being in Sidoarjo Hospital by 11 mothers . 2%). History of abortion in the second trimester, indicated that the average history of preterm birth abortion was significantly different between hospitals, i. , mothers who did not have a history of abortion had an average of 15 mothers per hospital, with the highest number at the Jemur sari was 24 mothers . 9%) and mothers who have a history of abortion have an average of 1 mother per hospital, with the highest number in Sidoarjo Hospital by 4 mothers . 0%). The number of ANC visits during pregnancy, indicated that the average number of ANC visits during pregnancy preterm labor was significantly different between hospitals, namely mothers who visited ANC >4 times during pregnancy had an average of 13 mothers per hospital. With the highest number in Airlangga Hospital by 22 mothers . and mothers who visited ANC <4 times during pregnancy had an average of 3 mothers per hospital, with the highest number being in Jemur Sari and Sidoarjo hospital which was 6 mothers each . 5%). According to the Ministry of Health . at least 4 visits during pregnancy, namely first trimester one visit . efore 14 weeks gestatio. , second trimester one visit . efore 14-28 weeks gestatio. , third trimester two visits . estational age between 28-36 weeks and after gestational age> 36 week. Height, indicated that the average of preterm birth was significantly different between hospitals, i. , mothers who have height >145 cm have an average of 15 mothers per hospital, with the highest number in Jemur Sari and Airlangga Hospital by 23 mothers each . 2%) and mothers who have height <145 cm have an average of 1 mother per hospital and were found in all hospitals, except Madiun and Ngawi Hospital, there were no mothers have height <145 cm. BMI, indicated that the average preterm birth BMI was significantly different between hospitals, namely mothers who had a BMI of 5-25 Kg/m2 had an average of 11 mothers per hospital, with the highest number in Jemur Sari and Sidoarjo Hospital which were 20 mothers each . 9%) and mothers who have a BMI <18. 5 /> 35 Kg/m2 have an average of 5 mothers per hospital, with the highest number being in Jombang Hospital, there were 10 mothers . 5%). According to Oyston & Groom . that the risk of preterm birth occurs in mothers with BMI <18. 5 Kg/m2 when compared to normal maternal BMI (RR . , as well as mothers with a BMI> 35 Kg/m2 also increases the risk of preterm birth The history of preterm birth in previous pregnancies, indicated that the average history of preterm birth was significantly different between hospitals, i. , mothers who did not have a history of preterm birth had an average of 14 mothers per hospital, with the highest number in Jemur Sari Hospital has 20 mothers . 9%) and mothers who have a history of preterm birth have an average of 2 mothers per hospital, with the highest number in Jemur Sari Hospital and Sidoarjo Hospital, each with 5 mothers . 7%). Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 (OR 1. status of preterm birth was significantly different between hospitals, like mothers who have normal Hb: 10. 5-11 g/dl have an average of 11 mothers per hospital, with the highest number is in Jemur Sari and Sidoarjo Hospital which were 16 mothers each . 9%) and mothers who have abnormal Hb: <10. 5-11 g/dl have an average of 5 mothers per house sick, with the highest number in Airlangga Hospital by 12 mothers . 0%). MUAC, indicated that the average preterm birth BMI was significantly different between hospitals, i. , mothers who had MUAC >23. cm had an average of 11 mothers per hospital, with the highest number in the Jemur Sari and Sidoarjo Hospital, with 23 mothers each . 2%) and mothers who had <23. 5 cm MUAC had an average of 5 mothers per hospital, with the highest number in Jombang Hospital, namely 14 mothers . 4%). According to Shah et al. , . , the risk of preterm birth was higher in mothers who had MUAC O250 mm and showed less nutrition (RR: 1. CI 95%, 1. 17, 1, . BV status, indicated that the average BV status of preterm birth was significantly different between hospitals, i. , mothers who did not do BV had an average of 15 mothers per hospital, with the highest number at Jemur Sari Hospital by 25 mothers . 7%) and mothers who had done BV testing had an average of 1 mother per hospital, with the highest number in Jombang Hospital by 6 mothers . 5%). can increase the risk of premature 7 times, especially if it is found at <16 weeks of pregnancy (Robinson and Norwitz, 2. Periodontal infection, indicated that the average periodontal infection of preterm birth was significantly different among hospitals, , mothers who have experienced periodontal infection have an average of 13 mothers per hospital, with the largest number being in Airlangga Hospital that was 24 mothers . 9%) and mothers who had never experienced periodontal infections had an average of 3 mothers per hospital, with the highest number in Sidoarjo Hospital, by 10 mothers . 5%). According to Daalderop et al. based on reverage result his review for periodontal disease was 5% -38% for preterm birth and 6%-41% for LBW. Although according to Sutherland et al. , . that periodontal treatment did not affect preterm birth, so this study only gave different perondontal infection among hospitals, and not after given treatmeant during pregnancy. CONCLUSIONS There were significant disparities in maternal sociodemographic characteristics with preterm birth among hospitals. Sixteen variables of identified: gestational age, maternal age, smoking. EPDS, fetus less moving, number of visits during pregnancy, premature history, history of disease, a history of abortion, height. BMI. MUAC, periodontal infection, bleeding in young/old pregnancy, anemia and BV status. Our findings can be used as the basic data for future research in an effort to prevent premature birth disorders based on maternal sociodemographic characteristic. Bleeding young/elderly indicated that the average periodontal infection of preterm birth was significantly different between hospitals, i. , mothers who have never experienced bleeding in a young/elderly pregnancy have an average of 14 mothers per hospital, with the highest number found in Jemur Sari by 20 mothers . 9%) and mothers who had experienced bleeding in a young/old pregnancy had an average of 2 mothers per hospital, with the highest number in Sidoarjo Hospital by 8 mothers . 0%). Anemia status, indicated the average anemia ACKNOWLEDGMENTS The authors wish to thank and acknowledge . Kementrian Riset. Tekhnologi dan Pendidikan Tinggi Indonesia (Kemenristekdikti RI) for generously support in this project, . all midwives from Soewandhi hospital. Universitas Airlangga hospital. Islam Jemur Sari hospital. Sidoarjo hospital. Madiun Sogaten hospital. Jombang hospital. Ibnu Sina Gresik hospital, and Ngawi hospital for all valuable supports. Public Health of Indonesia. Volume 4. Issue 4. October - December 2018 AUTHOR CONTRIBUTIONS Purisch E Stephanie. Cynthia GyamA Bannerman. Epidemiology of preterm birth. Seminars in Perinatology, 41. , 387-391. Rallis S. Skouteris H. McCabe M, & Milgrom J. A prospective examination of depression, anxiety and stress throughout pregnancy. Women and Birth, 27. , e36Aee42. Robinson JN. Norwitz ER. Prematur birth: Risk factors and interventions for risk reduction. CharLockwood CJ . UpToDate Magazine, cited by April 17th 2017. Sastroasmoro S dan Ismail S. Dasar-dasar metodologi penelitian klinis edisi ke-5. Sagung Seto. Jakarta. Sentilhes Loyc. Julie Blanc. Marie-Victoire Synat. Gilles Brabant. Ducroux-Schouwey. Marcellin. PierreYves Ancel. Florence Bretelle. Anne Evrard. Styphane Marret. Patrick Rozenberg. Gilles Kayem. Nicolas Mottet. Thomas Schmitz. Elie Azria. Styphanie Brun. Guillaume Benoist. Muriel Doret. Emeline Maisonneuve. Sabine Paysant. Hyloyse Torchin. Chantal. Louis. Didier Riethmuller. Bruno Langer. Prevention of spontaneous preterm birth: Guidelines for clinical French College Gynaecologists and Obstetricians (CNGOF). European Journal of Obstetrics and Gynecology and Reproductive Biology, . Shaikh K. Premji SS. Rose MS. Kazi K. Khowaja S, & Tough S. The association between parity, infant gender, higher level of paternal education and prematur birth in Pakistan a cohort study. BMC Pregnancy and Childbirth, 11. , 1-10. Shah Rashed. C Mullany. Gary L Darmstadt. Ishtiaq Mannan. Syed Moshfiqur Rahman. Radwanur Rahman Talukder. Jennifer A. Applegate Nazma. Begum Dipak Mitra. Shams El Arifeen. Abdullah H Baqui. Incidence and risk factors of prematur birth in a rural Bangladeshi cohort. BMC Pediatrics, 14. , 1-10. Sutherland Melanie W. The Effect of Periodontal Treatment on Preterm Birth among Pregnant Women with Periodontal Disease: Utilizing Inverse Probability Weighting to Control for Selection Bias in a Randomized Controlled Trial. Annals of Epidemiology, 27. , 504-540. WHO. WHO Recommendations on interventions to improve prematur birth. WHO Press. WHO Library Cataloguing-in-Publication Data. Genewa Switzerland. SH contributed to data analysis, drafted the manuscript. SH. BS. HTD contributed to conception, design, and data analysis, critically revised the manuscript. All authors gave final approval and agreed to be accountable for all aspects of the project. 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