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Neonatal and Pediatric Medicine
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Determinants of Low Birth Weight among Mothers Who Gave Birth in Debremarkos Referral Hospital, Debremarkos Town, East Gojam, Amhara Region, Ethiopia

Tewelde Gebrehawerya1*, Kahsay Gebreslasie2, Endeshaw Admasu3 and Merhawi Gebremedhin3
1College of Medical and Health Science, Haramaya University, Harar, Ethiopia
2College of Health Science, Mekelle University, Mekelle, Ethiopia
3College of Medical and Health Science, University of Gondar, Gondar, Ethiopia
*Corresponding Author: Tewelde Gebrehawerya, College of Medical and Health Science, Haramaya University, Harar, Ethiopia, Tel: 00221775121402, Email: tewtsehaug20@gmail.com

Received: 15-Nov-2017 / Accepted Date: 02-Jan-2018 / Published Date: 09-Jan-2018 DOI: 10.4172/2572-4983.1000145

Abstract

Background: World Health Organization defines low birth weight as weight at birth of less than 2500 g. Low birth weight could be the result of either preterm birth or restricted intrauterine growth. Globally, out of 139 million live births, about 20 million of them are low birth weight and nearly 95.6% of them are in developing countries. Ethiopia, having an infant mortality rate of 59/1000 live births, has limited data on low birth weight estimates as most deliveries take place at home. According to Ethiopian Demographic and Health Survey, 2011, only 5% of children were weighed at birth. The aim of this study was to assess determinants of low birth weight in Debremarkos referral hospital.
Methods: Facility based case control study was undertaken from June to November 2015. The total sample size was 287 (191 controls and 96 cases). Data was collected through interview using structured questioner, actual measurements and review of clinical records. After checking for completeness and accuracy, data was entered in to Epi-info version 7 and was analyzed by SPSS version 20. Variables with P-value <0.2 in bivariate analysis were entered to multivariate analysis and variables with p-value <0.05, 95% CI were considered statistically significant.
Results: Cases and controls were similar in almost all socio demographic characteristics. About 79.2% of cases and 93.2% of controls had ante natal care at least once. However, majority of cases (73.7%) had ANC visit of three or less, whereas more than half of controls (59.6%) had four or more. Parity (AOR=4.93, 95% CI, 2.55-9.52), three or less ANC visits (AOR=3.81, 95% CI, 1.82-7.99), anemia (AOR=3.91, 95% CI, 1.73-8.87), hypertensive disorders (AOR=6.13, 95% CI, 2.69-13.98) and frequency of meals per day (AOR=2.61, 95% CI, 1.26-5.38) were found significantly associated with low birth weight.
Conclusions: Parity, three or less ante natal care visits, anemia, hypertensive disorders of pregnancy and frequency of meals per day were found significantly associated with low birth weight. Emphasis should be given to ante natal service utilization, prevention of anemia, early detection and management of hypertensive disorders and feeding practice of pregnant women.

Keywords: Determinants; Low birth weight; Case control; Debremarkos; Ethiopia

Introduction

World Health Organization (WHO) defines low birth weight (LBW) as weight at birth of less than 2500 g. LBW could be the result of either preterm birth or restricted intrauterine growth [1]. Globally, out of 139 million live births about 20 million of them are low birth weight and nearly 95.6% of them are in developing countries [2]. LBW contributes substantially to neonatal, infant and childhood mortality and morbidity [3]. Globally neonatal mortality is 20 times higher among LBW babies compared to their counter parts [4]. Evidences also reveal that LBW babies are likely to have disabilities such as poor schooling, hospitalization, poor language development and intellectual impairments [1,5].

Evidences reveal magnitude of LBW to be significantly different across the world. It is highest in South Asia (31%) and lowest in East Asia (7%). In sub-Saharan Africa and Middle East/North Africa it is reported to be 14% and15% respectively [6].

Ethiopia, having an infant mortality rate of 59/1000 live births, has limited data on LBW estimates as most deliveries take place at home. According to Ethiopian Demographic and Health Survey, 2011, only 5% of children were weighed at birth [1,5]. Better understanding of LBW causes is essential for designing cost effective intervention strategies aimed at reducing LBW rates. This study is therefore aimed at assessing determinants of low birth weight in the study area which might be helpful to design preventive strategies.

Methods

This study was conducted in Debremarkos referral hospital, East Gojam zone, Northern Ethiopia, located 300 km northwest of Addis Ababa. The town is divided in to 7 kebeles with estimated total population estimated of 62,469. The town has one referral Hospital, three health centers, three private clinics and one family guidance association (FGA) [7]. The referral hospital catchment population is estimated to be 5 million. The study was conducted from June to November 2015.

Facility based unmatched case-control study design was utilized. Source population was all women who gave live birth in the study facility while study population was all mothers who gave birth to live single ton baby during the data collection period [8-10]. All mothers who gave birth to live singleton baby during the study period were included whereas mothers with: preterm baby, unknown last normal menstrual period (LNMP) and/or have no early ultrasound examination or early urine test, gave birth a baby with serious visible congenital anomalies and macrosomic newborns (baby weighing ≥4000 g were excluded from the study [11-13]. Sample size was calculated using Epi Info version 7 with the assumption of P1=14.4% (proportion of controls with no ANC follow up), P2=29.8% ( proportion of cases with no ANC follow up), 95% CI, Power of 80%, and case to control ratio of 1:2 (Table 1). The sample size obtained considering the above assumptions was 273 (91 for cases and 182 for controls). Adding 5% non-response rate, the total sample size was 287; which is 96 cases and 191 controls. Cases were operational defined as mothers who gave birth to term live singleton baby weighing less than 2500 g whereas controls were mothers who gave birth to term live singleton baby weighing ≥2500 g and <4000 g. Additional food during pregnancy was defined as intake of at least two additional meals per day during the pregnancy [14,15].

Variable  Case n (%)=96  Control n (%)=191
Age
<19 15 (15.6%)  8 (4.2%)
20-29 68 (70.9%) 151 (79%)
≥30 13 (13.5%) 32 (16.8%)
Occupation
Housewife 76 (79.2%) 140 (73.3%)
Merchant 1 (1%) 18 (9.4%)
Government employee 12 (12.5%) 33 (17.3%)
Others 7 (3.1%) 0 (0.0%)
Marital status
Married 78 (81.25%) 177 (92.7%)
Separated 8 (8.33%) 14 (7.3)
Widowed 6 (6.25%) 0 (0.0%)
Single 4 (4.12%) 0 (0.0%)
Residence
Urban 42 (43.8%) 95 (49.7%)
Rural 54 (56.2%) 96 (50.3%)
Religion    
Orthodox 75 (78.1%) 156 (81.7%)
Muslim 16 (16.7%) 29 (15.2%)
Protestant 5 (5.2%) 6 (3.1%)
Ethnicity
Amhara 96 (100%) 190 (99.5%)
Tigray 0 (0%) 1 (0.5%)
Educational status
Cannot read and write 53 (55.2%) 97 (50.8%)
01-Aug 19 (19.8%) 21 (11.0)
09-Dec 12 (12.5%) 36 (18.8%)
Diploma and above 12 (12.5%) 37 (19.4%)
Family size 
≤3 49 (51.0%) 82 (42.9%)
04-Jun 28 (29.2%) 98 (51.3%)
≥7 19 (19.8%) 11 (5.8%)
Family monthly income
≤600 43 (44.8%) 61 (31.9%)
700-1500 34 (35.4%) 47 (24.6%)
1600-2500 15 (15.6%) 44 (23%)
≥2600 4 (4.2%) 39 (20.4%)

Table 1: Socio demographic characteristics of study participants in Debremarkos Referral hospital, East Gojam, Amhara region, Ethiopia,2015.

All term singleton low birth weight babies born during the study period were taken as cases and the next two consecutive term singleton normal birth weight newborns were taken as controls. Data was collected through interview using structured questionnaire, reviewing maternal records/carts and actual measurement of some variables. Data collection tool prepared in English was translated in to local language Amharic for data collection and back to English for analysis. Three diploma and one BSc midwives were involved to collect data [16-19]. Data was collected in the immediate post natal period. Height of mothers was measured with height scale in centimeter while the mother is in standing position and bare feet, and was recorded nearest to 0.1 cm. Gestational age was calculated using last normal menstrual period and review of maternal record of early ultrasound examination or urine test.

Weight of babies was measured using neonate scale beam balance machine and babies were weighed naked and weight was recorded to the nearest of 100 g. Weighing machine was checked and zeroed before weighing each baby. Weight of baby was taken within 1-2 h postdelivery. Collected data was reviewed and checked for completeness and consistency on daily basis [20-23]. Training on data collection, interviewing approach and measurement of height of mother and weight of baby was given to all data collectors and supervisor. Pre-test was done on 5% of the total sample size in Finote selam hospital before actual data collection was started and necessary corrections were made accordingly.

After data was checked for completeness and consistency, it was entered in to computer using Epi info version 7 and then exported in to SPSS version 20. Further cleaning and recoding was done before analysis. Descriptive statistics like frequencies, cross tabulation, proportion, Mean and standard deviation were computed. Bivariate analysis using binary logistic regression was done to see association between dependent and independent variables (Table 2).

Variables Birth weight COR (95% CI) AOR (95% CI)
Case (n=96) Control (n=191)
Family income ≤1500 77 120 2.40 (1.34-4.29)  
>1500 19 71 1.00  
Parity Primi 49 58 2.39 (1.44-3.96) 4.93 (2.55-9.52)
 Multi 47 133 1.00 1.00
Pregnancy intended Yes 74 167 1.00  
No 22 24 2.07 (1.09-3.92)  
ANC status ≤3 times 76 85 4.74 (2.68-8.37) 3.81 (1.82-7.99)
≥4 times 20 106 1.00 1.00
Anemia (hemoglobin level) <11mg/dl 26 17 3.80 (1.94-7.44) 3.91 (1.73-8.87)
≥11mg/dl 70 174  1.00 1.00
Iron and folic acid supplementation Yes 74 175 1.00  
No 22 16 3.25 (1.62-6.54)  
Disease condition during pregnancy No 57 153 1.00 1.00
Hypertensive disorders 29 16 4.87 (2.46-9.62) 6.13 (2.69-13.98)
Others 10 22 1.22 (0.54-2.73)  
Number of meal per day ≤3 times 65 72 3.47 (2.06-5.82) 2.61 (1.26-5.38)
≥4 times 31 119 1.00 1.00

Table 2: Bivariate and multivariate logistic regression analysis of variables in relation to LBW among cases and controls in Debremarkos Referral Hospital, East Gojam, Amhara region, Ethiopia, 2015.

All variables with P-value <0.2 in bivariate analysis were entered into multivariate logistic regression model. Association between dependent and explanatory variables was assessed using AOR, 95% CI. Variables with P-value <0.05 were considered statistically significant.

Ethical clearance was obtained from University of Gondar Institutional Research Ethics Review Committee. Formal letter was submitted to all the concerned bodies in the study area to obtain their co-operation in facilitating the study. Data collectors explained the objective, benefit and risks of the study to the study participants to get informed consent prior to data collection. Respondents were told they have the right to refuse or decline from the study at any time if they wish so. Study participants were also explained for the attainment of confidentiality and the information they give will not contain their name or any identifiers and would not be used for any purpose other than the study.

Result

A total of 287 mothers were included in this study (191 controls and 96 cases). There was no non response rate. The mean age and standard deviation of study participants’ among cases was 24.57 ± 5.02 while that of controls was 25.39 ± 4.87. Majority of cases and controls (70.9%, 79%) respectively fall to the same age group (20-29). Almost all (99.5%) were Amhara and majority were house wife, married, orthodox and illiterate in both cases and controls. About half of cases (51%) had family size of three or less while equal magnitude of controls had four or more family size. Majority of cases (80.2%) had an income of less than or equal to 1500 Ethiopian birr whereas only about 56.5% controls belong to the same income level.

About 51% of cases were primi parous and 70.6% of controls were multi parous. About 79.2% of cases and 93.2% of controls had ante natal care at least once. However, majority of cases (73.7%) had ANC visit of three or less, whereas more than half of controls (59.6%) had four or more. Less than half (46.7%) of the cases had first visit at first trimester unlike to controls where majority (71.3%) had first visit at first trimester.

Among cases who had ante natal record of first trimester weight (52.1%), about two third (64%) of them had weight of 50.5 kg and above, while this was also true for majority (88.7%) of the controls. The mean and standard deviation of weight gain during pregnancy for cases and controls was 4.59 ± 1.26, and 6.2366 ± 1.41 respectively. BMI was calculated for nearly half (47.9%) of cases and more than two third (69.6%) of controls. Majority of both cases (82%) and controls (93.2%) fall to normal range. The proportion of underweight was higher among cases (18%) than controls (3%). About 77.1%, 87.4% pregnancies among cases and controls respectively were intended. Proportion of disease condition during pregnancy among cases was about twice higher than controls (40.6%, 19.9%) respectively. Hypertensive disorders of pregnancy accounts for 71.8% of the diseases among cases.

About 70.75% of controls had additional food intake and 62.3% of them greater than four time a day meal. However, 60.4% of cases had no additional food intake and about two third of them (67.7%) had three times or less a day meal.

The mean birth weight of babies among cases and controls was 2171.9 ± 136.7 and 3082.1990 ± 2221.8999 g respectively. Female sex was dominant in both cases and controls (71.9%, 61.3%) respectively.

Family monthly income, parity, pregnancy intention, ANC service utilization, anemia, iron and folic acid supplementation, hypertensive disorders of pregnancy and frequency of meal per day were found to be associated with low birth weight in binary logistic analysis.

All variables with P-value <0.2, 95% CI, in bivariate analysis were entered in to multivariate analysis. Parity, Anemia, ANC service utilization, hypertensive disorders of pregnancy and Frequency of meals per day were found to have statistically significant association with low birth weight (P-value <0.05, 95% CI).

Primigavida mothers were about five times more likely to give low LBW than multi parous mothers (AOR=4.93, 95% CI, 2.55-9.52). Although majority of both cases and controls had normal hemoglobin level, the proportion of Hgb <11 mg/dl was higher among cases than controls. Women with Hgb <11 mg/dl were about three times more likely to give LBW baby than their counter parts ( AOR=3.91, 95% CI, 1.73-8.87).

Proportion of hypertensive disorders of pregnancy was also about four times higher in cases than controls [24-29]. Mothers who have hypertensive disorder during pregnancy were about six times more likely to give LBW baby than those who have no the disease (AOR=6.13, 95% CI, 2.69-13.98). The proportion of cases and controls that had ANC service utilization of three or less was 79.2% and 44.5% respectively. Mothers who had three or less visit were about five times more likely to give LBW than who had four and above visits (AOR=3.81, 95% CI,1.82-7.99).

Frequency of meals per day was also found to be significantly associated with LBW [30-33]. Mothers who had three or less times a day meal were about two and half times more likely to deliver LBW baby than those who had four and above meals per day (AOR=2.61, 95% CI, 1.26-5.38).

Discussion

The results of this study revealed that parity, hypertensive disorders of pregnancy, anemia (Hemoglobin <11 mg/dl), ante natal service utilization and frequency of meals per day were independently and significantly associated with LBW.

In this study, mothers who have had three or less ANC visits were about four times more likely to give LBW than those who had four and above visits. Similar finding was found in a study conducted in Axum, Tigray, Northern Ethiopia where mothers who had four and above ANC visits were 71% less likely to give LBW [7]. Facility based case control study done in India also revealed mothers who had ANC visit of three or less to be forty times more likely to give LBW than those who have greater than three visits [8]. Other studies done in University of Gondar referral hospital [9], kersa Demographic Health Research Center [6], Nigeria [10], Sudan [11] and India [12] also revealed ANC visits to be significant risk factors for low LBW. This may be due to the fact that ANC visits of the pregnant mother are very important to reduce adverse pregnancy outcomes including LBW as they provide chances for monitoring the fetal wellbeing and allow timely intervention by improving the health condition of the mother and preventing complications through early detection and treatment of complications [34-38].

Anemia during pregnancy was also found to have significant association with LBW, making anemic mothers about four times more likely to give LBW than their counter parts. This is supported by study done in Nigeria [10] where the proportion of LBW among mothers with anemia and without anemia was 60.5% and 39.5% respectively. Similar case control study conducted in India, karanka district hospital revealed anemic mothers to be about three times more likely to give LBW [13]. Other case control studies done in Sudan [11] and India [12] also conclude similarly. This might be due to the fact that babies born from anemic mothers get less oxygen and nutrients through the placenta.

A study conducted in Gondar town revealed pregnancy induced hypertensive disorders to be a significant risk factor for LBW [14]. Likewise, in this study, mothers with pregnancy induced hypertensive disorders were about six times more likely to give LBW than those who have no the disorder [39-44]. This finding is consistent with case control study conducted in India where mothers with pregnancy induced hypertensive disorders were about three times more likely to give LBW than their counterparts [12]. Matched case control study done in Malaysia also revealed mothers with hypertensive disorders to be about four times more likely to give LBW [15]. Retrospective study in west Algeria also revealed babies born from hypertensive mothers to be at higher risk of LBW (8.12%) than mothers with other disease [16].

Another study on risk factors among full term neonates in south India also reported similar finding [45]. This may be due to the fact that oxygen and nutrient supply through placenta is compromised as a result of the disorders.

This study also revealed primigavida mothers to be about five times more likely to give LBW baby than multi parous mothers. This is consistent with study done in Nigeria and Veintiane where primi parous mothers were about two times more likely to give LBW than multi parous mothers [46,47]. Case control study done in Malaysia also revealed primi gravida mothers to be three times more likely to have LBW baby [15]. This might be related to no prior experience to pregnancy events which might have positive or negative impact to birth weight. This study also showed mothers who had three or less meals per day were about two and half times more likely to give LBW than those who had four and above. This is against the WHO recommendation of frequency of meals per day for pregnant women which states at least two snacks between meals [2]. This might be due to limited food availability or poor awareness on the need for extra food during pregnancy.

Conclusion and Recommendation

Parity, Anemia, Hypertensive disorders during pregnancy, Ante natal service utilization and frequency of meal per day were found be independently and significantly associated with low birth weight. We would like to recommend zonal and regional health offices to design programs which can improve ANC utilization, anemia prevention, and feeding practice of all pregnant women.

Acknowledgement

The authors would like to express their deepest appreciation to the University of Gondar College of Medical and Health Sciences.

Authors’ Contribution

TG and KG designed and developed the proposal. They also supervised the data collection, analyzed the data and drafted the manuscript. EA and MG assisted the whole process from proposal development. They also reviewed and commented the manuscript. All authors read and approved the final manuscript.

References

  1. World health organization (2009) Bulletin of the world health organization.
  2. Wilcox AJ, Skaeven R (1992) Birth weight and perinatal mortality: the effect of gestational age. Am J Public Health 82: 378-383.
  3. Sa Ravi, Hatcher J, Qureshi R (2007) Maternal risk factors associated with low birth weight in karachi: a case control study. Eastern mediterranean health journal 13: 1343-1352.
  4. Lawn J, Lee A, Kinney M (2009) Two million intrapartum- related stillbirths and neonatal deaths: Where, Why and What can be done? Int J Gynaecol Obstet, 107: s5-s19.
  5. Badshah S, Mason l, Mckelvie K, Payne R, Lisbola PJG (2008) Risk factors for low birth weight in the public-hospitals at peshawer, NWFP pakistan. BMC public health 8: 197.
  6. Walden RV, Taylor SC, Hansen NI, Poole WK, Stoll BJ, et al. (2007) Major congenital anomalies place extremely low birth weight infants at higher risk for poor growth and developmental outcomes. Pediatrics 120: e1512-e1519.
  7. Valdez R, Athens MA, Thompson GH, Bradshaw BS, Stern MP (1994) Birth weight and adult health outcomes in a biethnic population in the USA. Diabetologia 37: 624-631.
  8. Ben-Shlomo Y, Smith GD (1991) Deprivation in infancy or in adult life: which is more important for mortality risk? Lancet 337: 530-534.
  9. Unicef/WHO (2008) Low birth weight, Country, Regional and Global estimates.
  10. Ethiopian central statistical agency: addisababa (2006) The 2005 ethiopian demographic and health survey (edhs) report. ethiopia Pp: 128-129.
  11. Dollberg S, Seidman DS, Armon Y, Stevenson DK, Gale RJ (2011) Adverse perinatal outcome in the older primipara. Perinatol 16: 93-97.
  12. LowaDepartment of Public Health; IOWA Department of Human Services, Factors Associated with Infant Low Birth Weight among Medicaid Reimbursed Births in IOWA, 2010.
  13. Ganesh Kumar S, Harsha Kumar HN, Jayaram S, Kotian MS (2010) Determinants of low birth weight: a case control study in a district hospital in Karnataka. Indian J Pediatr 77: 87-89.
  14. Strauss RS, Dietz WH (1999) Low maternal weight gain in the second or third trimester increases the risk for intrauterine growth retardation. J nutr (jev) 129: 988-993.
  15. Lawoyin TO (1997) The relationship between maternal weight gain in pregnancy, hemoglobin level, stature, antenatal attendance and low birth weight. Southeast asian j trop med public health 28: 873-876.
  16. Agarwal A, Ahmad S, Goel K, Kumar V, Goel P, et al. (2012) Maternal risk factors associated with low birth weight neonates in a tertiary care hospital, Northern India. J Community Med Health Educ 2:177.
  17. Metgud CS, Naik VA, Mallapur MD (2012) Factors affecting birth weight of a newborn - A community based study in rural Karnataka, India. Plos one 7: e40040.
  18. Deshmukh JS, Motghare DD, Zodpey SP, Wadhva SK (1998) Low birth weight and associated maternal factors in an urban area. Indian Pediatr 35: 33-36.
  19. Mbuya MNN,Chidem M, Chasekwa B, Mishra V (2010)Biological, social, and environmental determinants of low birth weight and stunting amonginfants and young children in Zimbabwe.
  20. Mumbare SS, Maindarkar G, Darade R, Yenge S, Tolani MK, et al. (2011) Maternal risk factors associated with term low birth weight neonates: A matched-pair case control study. Indian Pediatrics 49: 25-29.
  21. Das Gupta A, Basu R (2011) Determinants of low birth weight in a block of hooghly, west bengal: a multivariate analysis. International journal of biological & medical research. Int J Biol Med Res 2: 838-842.
  22. Siddhi S, HirveBela R, Ganatra (1994) Determinants of low birth weight: a community based prospective cohort study, in pune district surveys. Indian Pediatrics 31: 1222-1225.
  23. Van Roosmallen J (1988) Birth weights in two rural hospitals in the united republic of Tanzania. Bull who 66: 653-658.
  24. Negi KS,Kandpal SD,Kukreti M (2006) Epidemiological factors affecting low birth weight.
  25. Berihun MZ, Zelalem M, Mohammed N (2012) Incidence and correlates of low birth weight at are ferral hospital in north west Ethiopia, Pan African Medical Journal 12: 4.
  26. Boo NY, Lim SM, Koh KT, Lau KF, Ravindran J (2008) Risk factors associated with low birth weight infants inthemalaysian population. Ed J Malaysia 63: 306-310.
  27. Bhatti A, Naz S, Majid E, Bhatti N (2010) Maternal risk factors associated with low birth weight babies. Medical channel 16: 334-338.
  28. Paneru DP, Naik VA, Nilgar B, Mallapur MD (2014) Obstetric risk factors for low birth weight amongst full term babies born at a tertiary care hospital of belgaum district, South India. Community Med 5: 81-84.
  29. Rizvi SA, Hatcher J, Jehan, Qureshi R (2007) Maternal risk factors associated with low birth weight in Karanchi Pakistan, a case control study. Eastern Mediteranean Health Journal.
  30. Agarwal K, Agarwal A, Agrawal VK, Agrawal P, Chaudhary V (2011) Prevalence and determinants of “low birth weight” among institutional deliveries. Ann Nmed 5: 48-52.
  31. Elhassan M, Ameer OA, Abderahuim DH, Abubaker MS, Adam J (2010) Anaemia and low birth weight in Medani, hospital Sudan. BMC Research Notes 3: 181.
  32. Assefa N, Berhane Y, Worku A (2012) Wealth status, mid upper arm circumference (muac) and ant atal care (anc) are determinants for low birth weight in Kersa, Ethiopia. PLoSOne 7: e39957.
  33. Schultz R, Read AW, Straton JA, Stanley FJ, Morich P (1991) Genitourinary tract infections in pregnancy and low birth weight: case-control study in Australian aboriginal women. BMJ 303: 1369-1373.
  34. Shore R, Iowa department of public health, Lowa department of human services (2010) factors associated with infant low birth weight among medicaid reimbursed births in iowa.
  35. Dejin-Karlsson E, Hanson BS, Ostergren PO, Sjoberg NO, Marsal K (1998) Does passive smoking in early pregnancy increase the risk of small-for-gestational-age infants?. Am J Public Health 88: 1523-1527.
  36. Teklehaimanot N, Hailu T, Assefa H (2014) Prevalence and factors associated with low birth weight in axum and laelaymaichew districts, North Ethiopia: A comparative cross sectional study. International Journal of Nutrition and Food Sciences 3: 560.
  37. Dalal A, Chauhan S, Bala D (2014) Epidemiological determinants of low birth weight in Ahmedabad city: A facility based case-control study. International Journal of Medical Science and Public Health 3: 430-432.
  38. Zenebe K, Awoke T, Birhan N (2014) Low birth weight & associated factors among new borns in Gondar town, North West Ethiopia: Institutional based cross-Sectional study. Indo Global Journal of Pharmaceutical Sciences 4: 74-80.
  39. Sutan R, Mohtar M, Mahat AN, Tamil AM (2014) Determinant of low birth weight infants: a matched case control study. Open Journal of Preventive Medicine 4: 91-99.
  40. Beddek F, Demmouche A, Mai A, Ghani A, Benali A (2014) Low birth weight in sidibel abbes region (west of algeria): retrospective study of 10008 deliveries. J Blood Disorders Transf5: 2.
  41. Ugboma H, Onyearugha C (2013) Low birth weight delivery: prevalence and associated factors as seen at a tertiary health facility. Nigerian journal of clinical practice 16: 184-187.
  42. Barua A, Hazarika J, Dutta S (2014) Correlates of low birth weight a hospital-based study from gangtok, india. Global Pediatric Health 1: 2333794x14562229.
  43. Louangpradith V, Yoshitoku Y, Md Harun-Or-Rashid, Sakamoto J (2010) Factors affecting low birth weight at four central hospitals in Vientiane. Lao Pdr J Med Sci 72: 51-58.
  44. Kramer MS (1987) Determinants of low birth weight: methodological assessment and meta-analysis. Bulletin of the world health organization 65: 663-737.
  45. Siza JE (2008) Risk factors associated with low birth weight of neonates among pregnant women attending a referral hospital in northern Tanzania. Tanzania Journal of Health Research 10: 01-08.

Citation: Gebrehawerya T, Gebreslasie K, Admasu E, Gebremedhin M (2018) Determinants of Low Birth Weight among Mothers Who Gave Birth in Debremarkos Referral Hospital, Debremarkos Town, East Gojam, Amhara Region, Ethiopia. Neonat Pediatr Med 4: 145. DOI: 10.4172/2572-4983.1000145

Copyright: © 2018 Gebrehawerya T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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