Preterm birth: associated risk factors in the tertiary care center 1Mrs Sweety Jousline Fernandes, 2Dr Tessy Treesa Jose, 3Dr Judith Angelitta Noronha,4Dr Sushmitha R Karkada (1. MSc (N), MPhil(N), Asst Professor, OBG Dept., MCON Manipal, Karnataka, India. 2.MSc (N), Ph.D. (N) Professor and Head, Dept of Psychiatry (N), MCON Manipal, Karnataka, India. 3. MSc (N), MPhil. (N), Ph.D. (N), Associate Dean, Professor & Head Dept of OBG (N) MCON, Manipal, Karnataka, India, 4. MSc (N), Asst Professor(Sr Scale), OBG Dept., MCON Manipal, Karnataka, India)Abstract:Objective: The study aimed at identifying the prevalence of preterm labor and the associated risk factors.Design: A quantitative approach using retrospective case control study. Setting: Tertiary care hospital of Udupi district Karnataka. Population or Sample: Women delivered in tertiary care hospital of Udupi district Karnataka were the sample, among them the cases (250) were the records of the women who had delivered before 37 weeks of gestation and controls (500) were the records of women who delivered after 37 weeks of gestation and without any complications. Method: The study was conducted using, retrospective case-control design by reviewing the case records of women who had delivered in a tertiary care hospital. Main Outcome Measures: Women delivered in tertiary care hospital of Udupi district Karnataka, their inpatient records were assessed for the risk factors during the antenatal period and the period of delivery.Results: The study revealed that the prevalence of preterm labor was 356 (14.86%) Out of 2402 deliveries. Among them only 250 were assessed. It was significantly correlated with age, place of residence, degree of education, occupation, marital status, gravid para, and number of deliveries, type of deliveries, gap between births, blood type, and religion. Pregnant women who had been exposed or had risk for preterm labour included those who had been diagnosed with pregnancy-induced hypertension, medication during pregnancy, history of abortion, intense physical labour, and conception dates older than 30 years.Conclusion: The preterm labor prevalence can be minimized if the modifiable risk factors are in control. Non-Modifiable risk factors require keen supervision. Thus the health professional needs to be alert about all the modifiable and non-modifiable risk factors.Keywords: preterm labor, prevalence, risk factorsBackground: Preterm labor can be prevented if detected earlier, thus to determine the risk factors of preterm labor, the present study was conducted to identify preventive measures. The study was conducted in the tertiary care hospital of Udupi district using retrospective case-control design for identifying the prevalence and the risk factors of preterm labor by reviewing the case records of women who had delivered in a tertiary care hospital. The study revealed that the prevalence of preterm labor was 356 (14.86%) Out of 2402 deliveries. Among this 356 preterm labor, only 250 samples were assessed randomly for identifying the risk factors of preterm labor as per the sample size calculation. A significant association was found between preterm labor and age, residence, education level, occupation, marital status, gravid para (number of conception), number of deliveries, type of delivery, birth interval, blood group, and religion. The number of preterm labor were seen among the pregnant women who had been exposed and were proved to be at risk if they were diagnosed with pregnancy-induced hypertension, previous abortion, hard physical work, and age of conception above 30 years. The preterm labor prevalence can be minimized if the modifiable risk factors are in control. Non- Modifiable risk factors require keen supervision to prevent preterm labor.Keywords: preterm labor, prevalence, risk factorsIntroduction:A neonate who is born after 37 weeks itself requires a lot of attention and care as it steps into a different atmosphere after birth. The morbidity concerning preterm labor will continue in later life, which will result in physical, psychological, and economic costs. Globally, one out of 10 babies is born preterm. Approximately one million babies lose their lives every year because of complications of preterm births. Preterm labor is an obstetric emergency and a threat to population health. 75% of infant mortality is related to preterm labor. Preterm labor not only inflicts financial and emotional distress on the family, but it may also lead to permanent disability (physical or neural damages) in infants. The survival babies, express a periodic disability such as learning, visual and hearing difficulties. The preterm birth rate ranges from 5% to 7% of total live births in developed countries in comparison to developing countries. Over the last two decades, the preterm birth rate has remained unchanged or even risen in most countries, despite the increased understanding of possible risk factors and their pathological mechanisms. The pathway for the preterm labor is not clear in terms of whether it is because of the interaction of more than two pathways or is it the reason for the independent pathway. Commonly affecting factors for preterm labor include the health condition of the mother or fetus, genetic causes, exposure to the environment, treatment taken for infertility, habits, socioeconomic and iatrogenic factors. Preterm birth was the second leading cause of death in children under 5 years old. In 2010 there were approximately 3.1 million newborn deaths, out of them one-fourth of the death was in the first 24 hours after birth. Out of 184 countries, preterm birth is approximately 5 % to 18% of neonates born. In India out of 27million neonates born every year, 3.5 million are delivered prematurely. Antenatal period, labor process, and the postnatal period are the most critical period for the infant and maternal survival. Preterm labor is unpredictable but the cues can be identified and preventive measures can be taken. Physicians will make every effort to delay the delivery so that the baby can grow as much as possible. Therefore, one should not skip any important health details during the regular visit to the obstetrics clinic. The pregnant women should give a detailed history of once lifestyle, past pregnancies, any health issues which one had been through and get the doubts clarified. The statistics presented above along with the supported data helps obstetric care providers to design appropriate study and plan for measures to decrease the delivery rates before 37 weeks of gestation and to improve the health status of the women who have delivered. This will finally assist in reducing and filling the gaps between the study areas, as baseline information for other existing countries. To determine the risk factors of preterm labor, the present study was conducted to identify preventive measures. Medication intake during pregnancy, previous abortion which can be identified earlier and extra precautions to these risk factors can prevent preterm labor. There are modifiable risk factors like hard physical work and age of conception above 30 years which, if taken care of, can prevent preterm labor.Materials and Methods:A retrospective case-control study design was used to identify the prevalence and risk factors for preterm labor by assessing the case records of the women delivered in the tertiary care hospitals of the Udupi district. Cases for the study were women delivered before 37 weeks of gestation and controls were the women delivered after 37 weeks of gestation without any complication. A purposive sampling technique was used to select the records of 250 out of 356 women as per the sample size calculation who delivered in the year 2016.Procedure: The tools used were maternal socio-demographic proforma which consisted of 19 items. The structured Risk Assessment tool for preterm labor was developed by a researcher and it consisted of items that were classified as modifiable and non-modifiable risk factors. Modifiable risk factors had twenty-five items that were further subdivided into social factors, economic factors, and environmental factors. Non-modifiable risk factors had thirty-five items that were further subdivided as a medical condition, obstetrical condition, and fetal condition. The internal consistency of the tool was r=1. Permission was obtained from administrators and heads of departments of the institution Udupi district, ethical clearance was obtained from the Institutional Kasturba Medical College and Kasturba hospital, institutional Ethics Committee (IEC 30/2018). The study was registered with the Clinical Trial Registry of India (CTRI/2018/05/014078). Data analyzed using the “SPSS”16 version using descriptive and inferential statistics.Result: The study identified that the prevalence of preterm labor as shown in Figure 1 was 356 (14.82%) out of total 2402 deliveries. About background characteristics the cases and control varied as shown in table 1, with majority191 (76.4%) of them were residing in a rural area, maximum200 (80%) among the cases had occupation being housewives, many 189 (75.6%) were primi, thus the birth interval was not specified. The mean height among the cases as shown in table 2 among the cases was 154.32cm, in terms of mean age was 27.44 and the total weight gain of pregnant women during the pregnancy on an average was 7.67kgs among the cases (preterm deliveries). Among the controls (term deliveries) the majority 334 (66.8%) of them were residing in a rural area, maximum 250 (50%) among the cases had occupation being housewives, many 251 (50.2%) of pregnant women were pregnant for the second time with majority 292 (58.4%) of them had a birth interval of 1-2yrs. The mean height among the cases as shown in table 2 was 154.34cm, the mean age was 27.07 and the total weight gain during the pregnancy on an average was 7.54kgs. Thus it states that there is a high risk for preterm labor in the age group of 27 – 30 years if the women were homemakers and are from a rural area with the first pregnancy. Initially, univariate analysis was computed as shown in table 3 and then to get an accurate result by the adjusted odds ratio which was computed and depicted in table 4 which showed the factor that pregnant women had exposure to the risk factors like pregnancy-induced hypertension with the Odds ratio (OR) was 1.288 (CI 140.829,1.17), Medication intake during pregnancy with OR 62.406 (CI 7.599,512.513), previous abortion with OR 0.007 (CI.001,.066), hard physical work with OR.021(CI.002,.217), Conception age 30 and above with AOR 24.837(CI 2.648,232.965) had more chances of having preterm labor. After assessing the adjusted odds ratio, the data showed that the risk factors like pregnancy-induced hypertension (p=.001), medication intake (p=.001), and conception age at 30 or above (p= .005) are having chances of preterm labor which is significant at 0.005 level. Previous Abortion (p=.001) & hard physical work (p= .001) are statistically preventive factors but clinically it is not the preventive risk factors. The majority of the women among the cases and controls had taken medication like tab tibolone (steroids) and tab ceftriaxone (antibiotic) which has increased chances of having preterm labor.Discussion: Main findings: Description of sample characteristics in frequencies and percentage: Majority of the pregnant women both among cases and controls are residing in rural area 191(76.4%) and 334 (66.8%), Most of the women’s educational status is not mentioned as, many of the women’s in both the groups are housewives (case 200 (80%) and controls 250 (50%)), All the women in both the groups were married and were with their spouses. Majority of the women among cases were primi 189 (75.6%) and majority of them 251 (50.2%) of pregnant women among control were pregnant for the second time. Majority among the cases had delivered once 189 (75.6%) and maximum among the controls delivered twice 333(66.6%). Among the Cases majority were Primi so the birth interval was not specified and among the controls majority 292 (58.4%) of them had birth interval of 1 – 2yrs. All the women’s in both the group had regular follow up and had taken supplements as specified. The mean age of cases, is 27.44 followed by the mean age for controls was 27.07. The mean height for the cases was 154.32cm and control group is 154.34cm. The total weight gain of pregnant women during the pregnancy on an average was 7.67kgs and that of control is 7.54kgs. Additional information on Blood grouping and religion was collected, Were by majority among the cases were belonging to O+ 111 (44.4%) blood group and among the controls majority had A+ 209 (41.8%) blood group.Among both the group, cases and control were belonging to the Hindu religion i.e. 227 (90.8%) and 375 (75%) respectively.Prevalence of preterm labor in tertiary care hospital of Udupi district Karnataka: Out of 2402 deliveries in Tertiary care hospital of Udupi district Karnataka. 356 (14.82%) were preterm labor and maximum number 2046 (85.17%) were term deliveries irrespective of their mode of deliveries.Association between selected variables and the preterm labour: There is association with the age (p= .002), residence (p= .001), education level (p=.001), occupation (p=.001), marital status (p=.004), gravida (p=.001), number of deliveries (p=.001), type of delivery (p=.001), birth interval (p=.001), blood group (p=.001) and the religion (p=.001). But there is no association between Height and weight gain during pregnancy. Thus it states that there is high risk for the preterm labor at the age ranging from 27 – 30 years, if the women are from rural area, being at home with primi para.The pregnant women had exposure to the pregnancy induced hypertension AOR 1.288(CI 140.829,1.17), Medication intake during pregnancy AOR 62.406(CI 7.599,512.513), Abortion AOR.007(CI.001,.066), hard physical work AOR.021(CI.002,.217), Conception age 30 and above AOR 24.837(CI 2.648,232.965) has chances of having preterm labor.After assessing the Adjusted Odds ratio, the data shows that the risk factors like pregnancy induced hypertension (p=.001), medication intake (p=.001) and conception age at 30 or above (p= .005) are having chances of preterm labor which is proved significantly at the level of .005. Previous Abortion (p=.001) & hard physical work (p= .001) are proved statistically as the preventive factors but clinically it is not. The majority of the women among the cases and controls had taken only tidalone and ceftriaxone which may be the reason for the chances of having preterm labor. Betamethasone intake is excluded because it is a drug of choice for lung maturity in case if the women comes with preterm labor pain. This is the drug of choice for prevention of preterm labor.Limitations: The limitations of the study are:As the present study is retrospective, the data was based on availability of information in the recordsWomen with preterm labour in Kasturba hospital were only included for the studyPurposive sampling technique was used so the generalization of the study is difficult.InterpretationThe data in the study show that 356 (14.82%) women delivered before 37 weeks of gestation among the total 2406 deliveries. The present study supports the finding of a cross-sectional study conducted on the Prevalence of preterm labor among young parturient women aged 15 – 24 years attending public hospitals in Brazil. The study findings revealed that the prevalence of preterm labor was 2071 (86.3%) out of 2400 parturient women. The maximum (36.1%) women with preterm labor were found in the northern region and the minimum (6.9%) number of preterm labor was found in the southern region, Results showed a high prevalence of preterm labor among young women in Brazil. Another retrospective study was conducted to identify the existence and reason associated with the occurrence of delivery before 37weeks of gestation in Jordan. The findings of the study showed that all the preterm deliveries were approximately 647. The maximum neonates were female than the males (54.9% Vs 45.1%), out of the maximum (75.6%) neonates were the second child, the women who delivered before 37weeks of gestation proper half were between the age group of 25–35 years of age. This is also supported by present study findings. The study finding showed an association between preterm and age (p= .002), residence (p= .001), education level (p=.001), occupation (p=.001), marital status (p=.004), gravida (p=.001), number of deliveries (p=.001), type of delivery (p=.001),birth interval (p=.001), blood group (p=.001) and the religion (p=.001) But there is no association between height and weight gain during pregnancy. Thus it states that there is a high risk for preterm labor if they are primipara, with conception age ranging from 27 – 30 years, residing in a rural area and homemakers. Similar studies findings are present like a retrospective cross-sectional study on the prevalence of preterm labor in a Labor room. It shows that the risk factors for early labor were active relationships during the previous week of labor, multiple pregnancies, the small birth intervals between two conceptions, PIH, fetal anomaly, premature rupture of membrane, and HTN. But the other aspects show that iron consumption, normal fetal presentation, blood-related problems, previous LSCS, prenatal care, and mother’s weight during pregnancy were considered as positive factors for the prevention of preterm labor. A case-control study was conducted by Barbara Luke et, al in the United States on the relation between the occupational factors and preterm delivery among the nurses. A total number of 210 nurses who had preterm labor and 1260 nurses who had delivered at term were included in the group. An occupational fatigue tool was used. Results showed that the risk factors related to preterm delivery included working hours per week (P=.002), different duty timings (p=.00l), standing hours (p=.001), noisy areas (p=.005), physical stress (p=.01) and work-related stress (p =.002). The result is the adjusted odds ratio was calculated for working hours per week were 1.6 (p=.006) and for fatigue was1.4 (p = 0.02). Preterm labor among the working women which can be a risk about the number of hours per day, week, and even extreme working condition. Using the results of this study and similar ones, to eliminate the risk factors and reinforce the protective factors would help decrease the rate of preterm labor and its human and social burden. Yet, for accurately determining these factors, studies with better design, such as cohort prospective studies, with proper follow-up period and large study population, are needed. Since the studied hospital is a referral center for these patients, it represents the general population of the country to a great extent. Still, the final decision regarding factors affecting pre-term labor should be made after further studies.Conclusion: The study concludes that preterm labor is commonly seen in pregnant women who are exposed to non-modifiable and modifiable risk factors. Modifiable risk factors can be avoided and thus allow the pregnancy to continue till term. Non-Modifiable risk factors need to be supervised very keenly so that there is no risk to the life of the mother and the fetus. It even states that the prevalence of preterm is more among the homemakers, thus these women need to be released from the level of stress which they are exposed to. All in all, the study concludes that these risk factors are different for each woman which will lead to preterm labor, but it needs to be identified at the earliest and needs to be treated adequately.Declaration :Principal Investigator: Mrs Sweety J Fernandes (role: Recrutment, data collection, rater, intervention provider, concept analysis, training provider and manuscript)Guide : Dr Tessy Treesa Jose (Role: Intellectual inputs , mentoring)Co – guide : Dr Judith A Noronha (Role: Intellectual, mentoring)Co- investigator: Dr Sushmitha R Karkada ( Role: Intellectual analysis)Funding statement: Manipal University provides the employees certain fund for research purpose so the same will be utilized for publication. PI has self funded for the studyAcknowledgement: I am greatful to the Hospital for giving the permission to get access to the records and greatful to the co investigators for their constant support and intellectual inputs