Proportion of Low Birth Weight Neonates and Associated Factors Among Mothers Delivered in Wolaita Sodo University Teaching and Referral Hospital, Ethiopia, 2018

Low birth weight continues to remain a major public health problem in Ethiopia in contrast to what is observed in many developing countries. The objective of this studt was to asses the proportion of low birth weight and associated factors among mothers who delivered in Wolaita Sodo University Teaching and Referral Hospital,2018. Retrospective cross-sectional study was employed. A total of 295 study participants were participated and selected by using systematic random sampling techniques. The data was entered and cleaned by Epi info version 7.0 and analyzed using SPSS version 20.0. Bivariate and multivariable logistic regression analysis was used.. Significance was declared at P<0.05 in a multivariable logistic interval with 95% of a confidence interval. The study indicated that 35(12.7%) of the mothers delivered low birth weight In multivariable analysis; Gestational age (AOR=12.203, 95%CI=4.695-31.716), primi (AOR=3.526, 95% CI =1.388-8.955), pregenancy type (AOR=3.491, 95% CI =1.063-11.464). Antenatal care visit (AOR=9.643, 95% CI=1.369-67.937). The finding of this study was low. The quality of cost-effective focused antenatal care, identifying obstetric complications and addressing them timely is recommended as to the occurrence of low birth weight could be minimized.


Introduction
World Health Organization (WHO), an infant is considered to be of low birth weight if his/her weight at birth is less than 2500 grams, irrespective of the gestational age of the infant. Classifications of Low Birth Weight (LBW) babies include low birth weight (less than 2500 grams), very low birth weight (less than 1500 grams) and extremely low birth weight (less than 1000 grams) [1].
The average newborn weights about 3500g. Babies of Low Birth Weight are at increased risk of short and long complicationsof health problems after birth. It is difficult for these babies to breastfeeding, increasing weight and fight infection. Because of their low body fat, it is also difficult for them to stay warm. Most of these low birth weight babies are required intensive neonate care care, usually in a Nursery [2].
Low birth weight is a major determinant of morbidity, mortality, and disability in infancy and childhood and has a long-term impact on health outcomes in adult life [3]. Women with low education, poverty and poor nutritional status who are increased risk of adverse reproductive outcomes including LBW and preterm birth. Therefore important to identify such mothers during pregnancy to determine the level of care and priorities for a referral to centers where reasonable obstetric and neonatal care is available [4]. The neonates of adult mothers are also more likely to have LBW with the risk of long-term effects [5]. Incidence of LBW ranged from 6% to 18% across the globe with Sub-Saharan Africa accounting13%to15% [6]. In Kenya, studies show that the proportion of low birth weight was 11.2% [7]. The prevalence of low birth weight vary from region to region in Ethiopia. For example, study conducted in Jimma reported that proportion of low birth weight was 22.5% [8] and a recent study in Gondar showed 17.1%. In Delivered in Wolaita Sodo University Teaching and Referral Hospital, Ethiopia, 2018 Ethiopia, there is limited information on birth weight distribution. Especially, there is no adequate information on the proportion and associated factors of low birth weight in the study setting. Therefore, this study aimed to assess the proportion and associated factors of low birth weight in Wolaita Sodo University Teaching and Referral Hospital.
The main purpose of this study was to provide baseline data on the proportion of low birth weight in the study setting and to identify possible factors for low birth weight were be help to inform the health authorities about the local associated factors for LBW.

Study Area
This study was done at Wolaita Sodo University Teaching Referral Hospital which is found 396 km south from Addis Ababa and 165km far from Hawassa, South Ethiopia.
The hospital is serving about three million people in the catchment area and people including in the neighboring zones. About 80,000 people visit Output patient department annually. The Hospital has 250 beds and 423 staff including specialists, general practitioners, X-ray technician, health officers, nurses, Midwives, laboratory professionals, pharmacists, druggists, and Administrative staffs. Out of these, 60beds inward, of Obstetrics / Gynaecology which 10 beds are in labor ward and 50 beds, are in Gynecology ward.
Obstetrics& Gynaecology department has its building with set up of Neonatal Intensive Care Unit, output patient department, Kangaroo mother care unit, Emergency output patient department, Antenatal care, Family planning, Laboratory, Delivery service unit, postnatal care unit, Obstetrics ward, Gynaecology ward, Operation room, Post anaesthetic care unit, and recovery unit. Regarding staff, the department has three Gynaecologists, 32 Midwives (BSC & Diploma) and there are also residents, IESO students and medical Interns currently practicing.

Study Design and Period
Institution based Retrospective cross-sectional study was conducted at Wolaita Sodo University Teaching & Referral Hospital, SNNPR, and Ethiopia among women delivering neonates from July 1, 2017, to 30 July 2018 G.C.

Sample Size Determination and Sampling Procedure
The sample size for this particular study was calculated using a formula for a single population proportion considering the following assumptions.
Prevalence of low birth weight and its Associated Factors among Mothers Delivered in Jimma University Specialized Teaching and Referral Hospital, Jimma Zone, Oromia Regional State, South West Ethiopia is found to be 22.5% [13], 95% CI, 5% marginal error, and 10% nonresponse rate.
(p = 22.5) was substituted in the following single population proportion formula. p=proportion of the problem (22.5%) d = an absolute precision (margin of error 5%). By adding 10% non-respondent rate for incomplete data, the required total sample sizes for the study was 27+268=295.
The Delivery register was used to obtain the sampling frame. Systematic sampling was used to enroll women in the study. Approximately 4536 women deliver at the hospital monthly, and since the study was conducted over four months, the total number of women who delivered over the months was expected to be 378. With a calculated sample size of 295, therefore the sampling interval was, k=N/n; were k = constant value, N = Source population = 4536, n=sample sizes=295 4536/295 = 15.
The interval was 15. The first sampling was chosen by lottery sampling method which start point was 10 using a random number delivery book, every 15 th delivery was selected until the desired sample size was achieved.

Data Collection Techniques
Information obtained from previous studies on low birth weight and other obstetrics and gynecology sites was used in addition to other variables, to design a structured questionnaire for data collection. Data was collect by using structured questionnaire from medical records of mothers, admission history, labour follow up sheet, delivery summary, antenatal care follows up sheet, Neonatal register book and Postnatal registration book used to get information for the study variables. This includes socio-demographic, Obstetrics factors, medical and health promotion factors and newborn factors. Beside principal investigator, there was one supervisor. The supervisor and data collectors were trained for a day on basic principles of data collection, on the questionnaire and how to do other related procedures during data collection by the principal investigator. Additional training on data completeness, cross-checking and correction actions was given to the supervisor. Accordingly, the supervisor continuously followed and supervised data collectors by collecting and cross-checking the completeness of questionnaires were received from data collectors and took corrective measures accordingly. And also reported and communicated with the principal investigator daily throughout the data collection period.

Exclusions
Medical records that have no explanation for gestational age were excluded.
Charts that did not have complete information relevant for the study were excluded.

Dependent Variables
Low Birthweight. Multiparous: Has had two or more deliveries that were carried to be viability.

Data Quality and Control and Data Analysis Procedures
The questionnaire was pre-test in around five percent of study subjects in WSTRH by taking Medical records of mothers who give birth from out of July 2017 to July, 2018G.C and was reviewed. To maintain data quality, giving trained for data collectors by the investigator's supervisor.
The questionnaire was pre-tested to check for the accuracy of responses and appropriateness of the data collection tool. Completeness and consistency by the principal investigator and supervisors on daily bases during data collection time.
The data was checked and entered using Epic-Info version 7.0. It was cleaned and edited accordingly and exported to SPSS Version 20.0 and checked for missing values before analysis. Descriptive statistics using the measure of central tendency and dispersion, frequencies, proportions, and diagrams were used to check its distribution and describe the study population with relevant variables.

Ethical Considerations
An official letter was written from Wolaita Sodo University College of Health Science and Medicine, Department of Neonatal and Paediatrics Nursing to Wolaita Sodo UniversityTeaching and Referral hospital chief clinical director office and to get permission from WSUTRH before collecting data from clients' charts.

Socio-demographic Characteristics
The purpose of the study is to examine the associated factors that contribute to low birth weight. Data were collected from hospital records of mothers who gave birth to babies in one year period of time. Therefore, availability sampling was used for the study. The data collected from the chart reviews were analyzed using descriptive statistics (frequencies and percentages).
A total of 295 records of women gave birth in the study setting were incorporated in the study. Of these, 19 (6.4%) in respondents were excluded which were invalid due to different reasons or errors in the review were intolerable. Therefore, from a total of 276 (93.5%) charts reviewed and included in the current study.
Regarding socio-demographic characteristics of mothers who given birth at the study setting about 60(21.7 %) were aged less than 20 years, 173(62.7%) were aged between 20-35 years and 43(15.6%) was aged above 35 years old. The majority 208(75.4%) of reviewed charts identified as Wolaita in their ethnicity whereas the list 68(24.6%) of them were others. More than half of the presence of women who give birth at the Hospital were from out of Sodo town whereas the rest resided of Sodo town. (See table 1

Obstetrics Factors
Regarding Obstetric characteristics, 268(97.1 % for women who have a history of Antennal care follow-up. From these, more than half mothers ANC follow up at WSUTRH, 86(31.2%) were followed up at other health facilities and the rest of mothers were no evidenced for ANC follow up. Among ANC followers, more than half of the mothers were multiparity and 114(41.3) were the first time delivery. Ninety-seven percent of mothers had received nutritional counseling. Even though, only 104 (37.7%) were exposure of Iron and folic acids during pregnancy.
From 276 mothers, more than eighty-five percent of the mothers were 37-42weeks gestation at the time of delivery and the rest of 35(12.7%) were preterm. Deliveries that completed by spontaneous vaginal deliveries were 221(80.1%) and cesarean section 55(19.9%).
The majority of the deliveries 250(90.6%) were single neonatal deliveries, 26 (9.4%) were Multiple deliveries. Obstetric complications were present in about 7.2% of women having a history of abortion was recorded in 4.7% of participant's pregnancies. From the total, current pregnancy 263 (95.3%) were planned and 13 (4.7%) were unplanned.
From total newborn, 131 (47.5%) male sex, 145(52.5%) females. From 276 mothers, the majority of them did not experience bleeding during pregnancy 269(97.5%) and only 7(2.5%) experienced bleeding during pregnancy. Nearly ninety-seven percents of mothers were not reporting having had a low birth weight baby in their previous pregnancy. Only 5(3.09%) mothers were reported having had reported a history of low birth weight. From the total, most of the mothers' weighted 50kg and above 249(90.2%) and 5(1.8%) of those mothers' weights were less than 50 kg whereas the rest of mothers were not recorded.

Antenatal Care Visits
From 276 mothers, more than half mothers who given birth at in Wolaita Sodo university teaching and referral

Associated Factors of Low Birth Weight
To see independent predictors of hospital delivery service, those factors found associated on a multivariable analysis involving all associated variables was performed to identify independent predictors of low birth weight. Consequently, gestational age, parity, pregnancy type and a woman who had ANC visit were independently showed significant association. The details are summarized on the table below.
A woman whose Gestational age was preterm had more likely to deliver low birth weight than those whose GA was a term. Women whose GA preterm were twelve times more likely to deliver low birth weight than women whos GA were a term (AOR=12.203, 95%CI=4.695-31.716).
Moreover, mothers who were primipara become three and half times more likely to deliver low birth weight than those who were multipara (AOR=3.526, 95% CI =1.388-8.955).
From the total of respondents, mothers who had multiple pregnancies were three and half times more likely to deliver low birth weight than those who had single pregnancy (AOR=3.491, 95% CI =1.063-11.464).
Women who had no ANC visit were more likely to deliver low birth weight than that of who had ANC visit. Mothers who had no ANC visit were nine and half times more likely to deliver low birth weight than women who had ANC visit (AOR=9.643, 95% CI=1.369-67.937).

Discussion
The proportion of low birth weight in this study was 12.7%. This Proportion was higher 7% documented in the developed countries [9]. Similarly, it was higher (9.1%) which was retrospective study conducted in Mother and Child Health clinics in three facilities in Korowai district, Tanzania [10]. Based on Ethiopian Demographic and Health Survey reports the proportion of LBW in Ethiopia estimated to be 11% [11]. The proportion was lower than 23% documented in Central Africa [12]. Also, it was lower 22.5% Jimma zone, Southwest Ethiopia [13]. But this result was similar to studies documented in Sudan [14]. Also, the study was nearly similar research conducted in all hospitals Addis Ababa indicated an LBW rate of [15]. Also, this difference may be the studies setting and sample sizes.
This study reveals that majority of the women delivering in Wolaita Sodo Teaching and Referral Hospital during the study period were aged 20-35 years. This finding was similar with findings documented elsewhere [16].
According to study coducted Kenya study, more than eight five percent of the mothers were from Rural residence [10]. A similar study conducted in Jimma zone, Southwest Ethiopia found 65 percent of the mothers attended the maternity facilities to be of rural residence [13]. In our study, More than half of the percent of mothers who gave birth at the Hospital were from rural residents than urban to similar to our findings.
In this study, some factors were found to be significantly associated with low birth weight on bivariate and multivariate analysis. They included having, gestational age (Preterm), parity, pregnancy type and a woman who had ANC visits.
In our study showed that preterm was 12 times more likely to be low birth weight compared to normal ones. A similar, study conducted in Tigray and Gondar University referral hospital the preterm baby was factors associated with LBW [17]. Study conducted in Pakistan showed that Preterm birth increased the risk of low birth weight six times compared to term babies [18]. The differences of this study from study conducted in Pakistan may be Sociodemographic status.
In our study, a lack of focused antennal care follows was nine times increasing low birth weight compared to focused antennal care followers. Similarly, Crossectional study conducted Jimma Zone, Southwest Ethiopia showed that Lack/infrequent of antenatal care follow-up was associated with LBW [13].

Conclusion and Recommendation
The proportion of low birth weight is low in this study. The associated factors of low birth weight were gestational age (preterm), parity, pregnancy type and a woman who had ANC visits may contribute to the occurrence of low birth weight. Therefore, the quality of cost-effective focused antenatal care identifying the medical illnesses as well as obstetric complications and addressing them timely is recommended as to the occurrence of low birth weight could be minimized.