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. 2018 Aug 25;11:611. doi: 10.1186/s13104-018-3723-9

Below normal birth weight in the Northwest part of Ethiopia

Wale Kumlachew 1, Nega Tezera 2, Aklilu Endalamaw 2,
PMCID: PMC6109272  PMID: 30144805

Abstract

Objectives

Low birth weight is one of the global agendas that have an impact on the short and long-term health status. A cross-sectional study from March 1 to April 1, 2018 was conducted. 381 mother–newborn pairs were participated. This study aimed to assess the prevalence and associated factors of low birth weight in the Northwest part of Ethiopia.

Results

The prevalence of low birth weight was 14.9% (95% CI 11.7–18.9). Being preterm [adjusted odds ratio (AOR) = 4.1; 95% CI 1.7–9.9], absence of ante-natal care follow-up (AOR = 3.4; 95% CI 1.2–9.5), malaria attack during pregnancy (AOR = 4.2; 95% CI 1.6–11.1), anemia during pregnancy (AOR = 2.6; 95% CI 1.03–7.0), and lack of iron supplementation (AOR = 4.0; 95% CI 1.3–12.6) were predisposing factors to low birth weight. On the other hand, infants born from employed mothers (AOR = 0.1; 95% CI 0.01–0.92) were less likely to born with below normal birth weight. The prevalence of low birth was high as compared to WHO estimation.

Keywords: Birth weight, Newborn, Ethiopia

Introduction

Low birth weight (LBW) is one of the reliable indicators and monitoring parameters of maternal and child health programs [1]. According to the world health organization (WHO) definition, LBW considered if weight at birth less than 2500 g [2].

Being below normal birth weight is the greater risk for different severe and life-threatening health complications. Notably, hypothermia, hypoglycemia, birth asphyxia, anemia, impaired nutrition, and respiratory problems are the major complications of LBW [3].

It is possible to prevent LBW prior to its occurrence. Accordingly, WHO sets a 30% reduction of LBW by 2025 through providing affordable, accessible, and appropriate healthcare services [4]. Accessing maternal education, expansion of antenatal care service, promoting planned pregnancy, preventing teenage pregnancy, increasing skilled birth attendants, and improving prenatal care services are implementing to prevent LBW [5].

Despite different healthcare services, LBW is continuing to be one of the important public health problems worldwide. Correspondingly, 15% to 20% of all births worldwide were LBW in 2014 [4]. It is also reported in Nepal (22.3%) [6], Nigeria (6.3%) [7], and Kenya (12.3%) [8]. Similarly, the prevalence of LBW is vary in different geographical areas of Ethiopia; 17.4% in Gondar Ethiopia [9], 11.1% in Southwest Ethiopia [10], and 9.9% in Northern Ethiopia [11]. The social and economic [12], maternal and infant-related factors of LBW are identified from other previous studies [12, 13].

There was no study found in the current study area related to LBW. Even if there are studies in other parts of the country, it cannot be represent the current study area due to the difference in demographic, socio-cultural, and other health coverage status.

Therefore, we aimed to assess the prevalence of low birth weight and its associated factors in the Northwest part of Ethiopia.

Main text

Methods

Study design, period, setting, and population

An institution based cross-sectional study was employed from March 1 to April 1, 2018, at two hospitals in the delivery clinics of Northwest part of Ethiopia. These hospitals are Assosa and Pawi general hospitals, where the majority of the population of the region gets healthcare services. Based on the current Ethiopian government classification, these hospitals are found in the Benishangul-Gumuz Region, which is located 632 km far from Addis Ababa. Based on the 2007 Census conducted by the Central Statistical Agency of Ethiopia [14], the Benishangul-Gumuz Region has a total population of 784,345. Of which, 398,655 were men and 385,690 were women. A lower percentage (13.51%) of the population were urban inhabitants [15]. According to 2016 EDHS report, the fertility rate of the region was 4.4% [16].

All mother–neonate pairs were the study population.

Sample size and sampling technique

The sample size is calculated using single population formula

n=za/22pq/d2.

where n is the desired sample size, Z is the standard normal distribution 1.96, P is the prevalence of low birth weight in Gondar Ethiopia (17.4%) [9], q is the proportion of the target population without the problem (1 − p), d is the 4% margin of error, n = (1.96)2(0.174) (0.826)/(0.04)2 = 346.

Considering 10% non-response rate, the total sample size is 346 + 35 = 381.

Participants were selected using proportional allocation; 241 samples from Assosa, and 140 from Pawi Hospital from the total of 710 mother–infant pairs. A systematic random sampling technique was conducted. Each participant was selected using (k ≈ 2) after providing a number to pregnant mothers attending delivery room from day one to the end of data collection. In situations, where a respondent did not agree or not met the inclusion criteria, the next random position would be considered.

Operational definition

Below normal birth weight: neonates whose birth weight less than 2500 g.

Data collection tools and procedures

Data was collected using a structured and pre-tested questionnaire, measurement, and chart review. The questionnaire was adapted from the Ethiopian demographic and health survey [16] and other literature. The questionnaire had three parts. The first part contains socio-demographic characteristics, the second part contains infant-related variables, and the third part contains maternal and obstetric-related variables.

Two diploma midwives and nurses who were working outside the study area collected the data. The weight of the newborn was measured after 30 min of delivery using a balanced weight scale. Maternal height was measured against a wall height scale to the nearest centimeter. Maternal weight was measured by beam balance to the nearest kilogram. Participants’ medical charts were reviewed to take some important variables like maternal hemoglobin level.

Data processing and analysis

Firstly, data were checked for completeness and inconsistencies. The collected data was entered into Epi-data version 4.2.0.0. and then exported to STATA version 14.0 for analysis. The socio-demographic distributions of the participants were described using descriptive statistics. Binary logistic regression analysis was applied. The multivariable logistic regression analysis was done for variables with a P-value less than 0.25 in the bivariable analysis. Those variables with P-value ≤ 0.05 were claimed as significantly associated factors of LBW.

Ethical considerations

Ethical clearance was obtained from the School of Nursing on behalf of the University of Gondar Institutional Ethical Review Committee. Written permission was taken to both Assosa and Pawi General Hospitals’ manager. Then, each respective manager wrote permission letter to the focal persons. Name or identification number of study participants was not recorded. Participant data was used only for the study purpose.

Result

Maternal socio-demographic characteristics

Three hundred seventy-five mother–neonate pairs have participated with a response rate of 98.4%. Mean age of mothers in this study was 27.19 ± 5.13 years. Of these, 72.53% mothers were between the ages of 20–35 years. About 45.6% of mothers were housewives. Regarding the residence, 33.33% were rural dwellers. The majority (41.87%) of mothers were diploma and above. The majority (30.13%) were Amhara ethnic group (Table 1).

Table 1.

Maternal demographic characteristics of mothers Assosa and Pawi hospitals, Northwest Ethiopia, 2018

Variable Frequency Percent
Maternal age (years)
 15–20 40 10.67
 20–35 272 72.53
 > 35 63 16.80
Marital status
 Married 265 70.67
 Single 54 14.40
 Divorced 25 6.67
 Widowed 31 8.23
Residence
 Rural 125 33.33
 Urban 250 66.67
Educational level
 Uneducated 106 28.27
 Up to secondary 112 29.87
 Diploma and above 157 41.87
Occupation
 Housewife 171 45.60
 Merchant 55 14.67
 Employ 109 29.07
 Student 40 10.67
Ethnicity
 Amhara 113 30.13
 Oromo 69 18.40
 Agew 30 8.00
 Shinasha 58 15.47
 Gumuz 26 6.93
 Berta 36 9.60
 Mao 19 5.07
 Komo 11 2.93
 Others 13 3.47

Association between LBW and socio-demographic characteristics

From the study participants, 56 were LBW, which makes the prevalence to be 14.93%. Mothers who were employed were significantly associated with LBW (AOR = 0.11; 95% CI 0.01–0.92) (Table 2).

Table 2.

The association between LBW and maternal demographic characteristics in Assosa and Pawi hospitals, Northwest Ethiopia, 2018

Variable LBW NBW Crude OR (95% CI) AOR (95% CI)
No. % No. %
Maternal age (years)
 15–20 8 14.29 32 10.03 1.59 (0.68, 3.71)
 20–35 37 66.07 235 73.67 1
 > 35 11 19.64 52 16.30 1.34 (0.64, 2.81)
Marital status
 Married 36 64.29 229 71.79 1
 Single 10 17.86 44 13.79 1.45 (0.67, 3.13)
 Divorced 5 8.93 20 6.27 1.59 (0.56, 4.50)
 Widowed 5 8.93 26 8.15 1.22 (0.44, 3.39)
Residence
 Rural 20 35.71 105 32.92 1.13 (0.63, 2.05)
 Urban 36 64.29 214 67.08
Educational level
 Uneducated 20 35.71 86 26.96 3.09 (1.41, 6.75) 1.06 (0.22, 5.06)
 Up to secondary 25 44.64 87 27.27 1 1
 Diploma and above 11 19.64 146 45.77 3.81 (1.79, 8.13) 1.72 (0.46, 6.43)
Occupation
 Housewife 31 55.36 140 43.89 1 1
 Merchant 8 14.28 47 14.73 0.77 (0.33, 1.79) 0.77 (0.23, 2.61)
 Employ 2 3.57 107 33.54 0.08 (0.02, 0.36) 0.11 (0.01, 0.92)
 Student 15 26.79 25 7.84 2.71 (1.28, 5.73) 1.03 (0.24, 4.38
Ethnicity
 Amhara 16 28.57 97 30.41 1
 Oromo 13 23.21 56 17.55 1.41 (0.63, 3.14)
 Agew 3 5.36 27 8.46 0.67 (0.18, 2.48)
 Shinasha 9 16.07 49 15.36 1.11 (0.46, 2.70)
 Gumuz 5 8.93 21 6.58 1.44 (0.48, 4.38)
 Berta 6 10.71 30 9.40 1.21 (0.44, 3.38)
 Mao 2 3.57 17 5.33 0.71 (0.15, 3.39)
 Komo 1 1.79 10 3.13 0.61 (0.07, 5.06)
 Others 1 1.79 12 3.76 0.51 (0.06, 4.16)

Association of obstetric history of mothers and newborn-related factors with LBW

Mother who did not have ANC follow-up (AOR = 3.45; 95% CI 1.25–9.55), mother who did not get iron tablet during pregnancy (AOR = 4.06; 95% CI 1.31–12.61), malaria attack during pregnancy (AOR = 4.28; 95% CI 1.65–11.14), and anemia during pregnancy (AOR = 2.69; 95% CI 1.03–7.01) are identified associated factors with LBW. Regarding neonatal-related factors, being preterm (AOR = 4.15, 95% CI 1.74–9.89) was associated with LBW (Table 3).

Table 3.

The association between LBW and maternal obstetric and neonate-related factors in Assosa and Pawi hospitals, Northwest Ethiopia, 2018

Variable LBW NBW Crude OR (95% CI) AOR (95% CI)
No. % No. %
Parity
 Multi-para 41 73.21 239 74.92 1
 Primi-para 15 26.79 80 25.08 1.09 (0.57, 0.08)
Maternal MUAC
 < 23 cm 9 16.07 41 12.85 1.30 (0.59, 2.85)
 ≥ 23 cm 47 83.93 278 87.15 1
Pregnancy
 Singleton 48 85.71 270 84.64 1
 Multiple 8 14.29 49 15.36 0.92 (0.41, 2.06)
History of abortion
 Yes 6 10.71 25 7.84 1.41 (0.55, 3.61)
 No 50 89.29 294 92.16 1
Number of ANC
 None 33 58.93 42 13.17 9.46 (5.07, 17.65) 3.45 (1.25, 9.55)
 One and above 23 41.07 277 86.83 1 1
Iron tablet
 Not taken 27 48.21 25 7.84 14.64 (7.09, 30.22) 4.06 (1.31, 12.61)
 Up to 1 month 11 19.64 50 15.64 2.98 (1.33, 6.70) 2.43 (0.83, 7.17)
 More than 2 months 18 32.14 244 76.49 1 1
Malaria
 Yes 35 62.50 33 10.34 14.44 (7.54, 27.67) 4.28 (1.65, 11.14)
 No 21 37.50 286 89.66 1 1
PIH
 Yes 3 5.36 14 4.39 1.23 (0.34, 4.4)
 No 53 94.64 305 95.61 1
Anemia
 Yes 28 50.00 37 11.60 7.62 (4.08, 14.25) 2.69 (1.03, 7.01)
 No 28 50.00 282 88.40 1 1
Previous LBW
 Yes 7 12.50 29 9.09 1.43 (0.59, 3.44)
 No 49 87.50 290 90.91 1
Confirmed DM
 Yes 1 1.79 6 1.88 0.95 (0.11, 8.03)
 No 55 98.21 313 98.12 1
Maternal weight
 < 50 kg 18 32.73 32 10.09 4.33 (2.21, 8.48) 2.37 (0.89, 6.35)
 ≥ 50 kg 38 67.27 287 89.91 1 1
Maternal height
 < 1.50 m 8 14.29 34 10.66 1.40 (0.61, 3.20)
 ≥ 1.50 m 48 85.71 285 89.34 1
Substance use
 Yes 0 0.00 0 0.00
 No 56 14.93 319 85.07
Maternal abuse
 Yes 0 0.00 0 0.00
 No 56 14.93 319 85.07
Gestational age (weeks)
 < 37 32 57.14 57 17.87 6.13 (3.36, 11.19) 4.15 (1.74, 9.89)
 ≥ 37 24 42.86 262 82.13 1 1
Sex of neonate
 Male 20 35.71 172 53.92 1 1
 Female 36 64.29 147 46.08 2.11 (1.17, 3.80) 1.76 (0.75, 4.12)

Discussion

Low birth weight prevalence varies in different geographical areas. Estimating the burden of LBW in the current study area was found to be relevant for the regional policy implementation and healthcare resources allocation. Accordingly, the prevalence of LBW was14.9% (95% CI 11.7–18.9). The finding of the current study was comparable with a study conducted in Tigray Ethiopia (14.6%) [17], Gondar Ethiopia (17.4%) [9], and southern Ethiopia (17.88%) [18].

On the other hand, it was higher than other Ethiopian settings, like Axum (9.9%) [11] and Jimma Ethiopia (11.02%) [10]. This might be due to the current study setting was a hospital setting where many chronic cases were referred from other health institutions but the others were community-based studies. Besides, the variation might be due to in the current study area was not well accessible for comprehensive health programs [16] and further due to cultural issues, in which one of the ethnic groups “Gumuz” population health seeking behaviors are poor. Besides, in “Gumuz” ethnic group, pregnant woman give birth alone and/or get away from around the peoples. The high malaria burden in the study area might be attributed to a high prevalence of LBW.

The current finding also higher than the finding from other African settings, like Nigeria [7], the United States of America [19], and Canada [20]. The possible explanation might be due to the difference in the level of antenatal care follow-up, the burden of food insecurity, the educational status of the community, cultural malpractices, and the high burden of co-morbid illness in Ethiopia.

Below normal birth weight is associated with the infant, maternal and obstetric related or environment and behavioral factors. Gestational age, malaria attack during pregnancy, anemia during pregnancy, the absence of ANC follow-up, and absence of iron intake during pregnancy were associated with LBW.

Regarding gestational age, preterm neonates were 4.2 times more likely to be LBW than term neonates. This finding was in agreement with a study done in Bale Ethiopia [21]. This might be due to the fact that as the gestational age of the fetus is lowered, prematurity and inadequate production of subcutaneous fat is prevalent [22].

The absence of ANC follow-up during pregnancy was another variable. Women had not ANC follow-up were 3.5 times more likely to give LBW baby than women who had ANC follow-up. The possible reason might be due to, in those who had no ANC follow-up, unable to detect early major health problems, pregnancy danger sign, and cultural malpractices that can affect the birth outcome of the neonate [23]. The other possible explanation might be those mothers who had no ANC visit during pregnancy may not receive iron supplementation and counseling about lifestyle and nutrition like food diversification during pregnancy to nourish the fetus for better growth and development during fetal growth [23].

Those mothers had history of malaria attack during pregnancy were 4.3 times more likely to deliver LBW baby than mothers had no history of malaria attack during pregnancy. This result is consistent with a study done in Gondar Ethiopia [9] and sub-Saharan Africa [24]. This might be due to long-standing infections during pregnancy has a direct effect to limit fetal growth. One of the pathological effects of malaria is prematurity. This is due to placental infection with malaria causes the placenta to carry antibodies, cytokines, and macrophages which later causes early initiation of labor [25].

This study found anemia was one of the risk factors of LBW. Anemic mothers had 2.7 times more likely of getting a LBW baby than non-anemic mothers. This finding is in agreement with a study done in Sudan [26]. This is because the lack of hemoglobin due to anemia leads to impaired nutrient and oxygen transport to the fetus through the maternal placenta and the normal fetal growth in the utero may compromise as a result. Moreover, anemia is one of the chronic outcomes of systemic infections, which had a direct effect on the intrauterine growth retardation [27].

Mothers who did not take iron during pregnancy were 4.1 times more likely of getting LBW baby than who took iron. A study in India [28] was agreed with this finding. Iron and folic acid can prevent the occurrence of anemia and has a positive effect on the supplementation of oxygen and nutrient to the fetus. The absence of utilizing iron and folic acid contribute to poor organ development [29]. Besides, according to the current study, mothers being employed either government or other private sectors were 89% protective to LBW.

This study found that the prevalence of LBW was still high compared with WHO goal by 2025 which is a 3% reduction every year from 2012 to 2025. Being preterm, lack of ANC follow-up, malaria attack during pregnancy, lack of iron supplementation, and employed mothers were associated factors of LBW.

Limitation

This study shares the limitation of cross-sectional study design and therefore, it does not show the seasonal variation of LBW.

Authors’ contributions

WK worked on designing the study, training the data collectors, supervising the data collectors, interpreting the result, preparing the manuscript. NT and AE participated on designing the study, critically reviewing the study, interpreting the result, and preparing the manuscript. All authors read and approved the final manuscript.

Acknowledgements

The authors acknowledge the Assosa University and the University of Gondar, Ethiopia for its financial support.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

Data will be available upon request from the corresponding author.

Consent to publication

Not applicable.

Ethical approval and consent to participate

Ethical clearance was obtained from an Institutional review committee of the School of Nursing, College of Medicine and Health Sciences, University of Gondar. Permission letter was obtained from each hospital administration. Verbal consent was also taken from mothers after the ethics committee approved it. Whenever participants age < 18 years, consent was obtained both from study participant and their mother.

Funding

Not applicable.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abbreviations

ANC

ante-natal care

AOR

adjusted odds ratio

EDHS

Ethiopian Demographic and Health Survey

LBW

low birth weight

MUAC

Mid Upper Arm Circumference

PIH

pregnancy induced hypertension

WHO

World Health Organization

Contributor Information

Wale Kumlachew, Email: kumlachewwale@gmail.com.

Nega Tezera, Email: tezera.nega@gmail.com.

Aklilu Endalamaw, Email: yaklilu12@gmail.com.

References

  • 1.OECD. Better policies for better lives-Social policy division: directorate of employment, labour and social affairs; 2017. http://www.oecd.org/. Accessed 11 Mar 2018.
  • 2.Lawn JE, Gravett MG, Nunes TM, Rubens CE, Stanton C. Global report on preterm birth and stillbirth (1 of 7): definitions, description of the burden and opportunities to improve data. BMC Pregnancy Childbirth. 2010;10(1):S1. doi: 10.1186/1471-2393-10-S1-S1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Hazzani FA, et al. Short-term outcome of very low-birth-weight infants in a tertiary care hospital in Saudi Arabia. Ann Saudi Med. 2011;31(6):581–585. doi: 10.4103/0256-4947.87093. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.World Health Organization. WHA global nutrition targets 2025: low birth weight policy brief. 2014. http://www.who.int/nutrition/topics/globaltargets_lowbirthweight_policybrief.pdf. Accessed 13 May 2018.
  • 5.Brief KCI . Preventing low birthweight. Baltimore: Annie E. Casey Foundation; 2009. [Google Scholar]
  • 6.Koirala AK, Bhatta D. Low-birth-weight babies among hospital deliveries in Nepal: a hospital-based study. Int J Women’s Health. 2015;7:581. doi: 10.2147/IJWH.S84559. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Oladeinde HB, Oladeinde OB, Omoregie R, Onifade AA. Prevalence and determinants of low birth weight: the situation in a traditional birth home in Benin City, Nigeria. Afr Health Sci. 2015;15(4):1123–1129. doi: 10.4314/ahs.v15i4.10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Muchemi OM, Echoka E, Makokha A. Factors associated with low birth weight among neonates born at Olkalou District Hospital, Central Region, Kenya. Pan Afr Med J. 2015;20:108. doi: 10.11604/pamj.2015.20.108.4831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Zenebe K, Awoke T, Birhan N. Low birth weight & associated factors among newborns in Gondar town, North West Ethiopia: institutional based cross-sectional study. Indo Glob J Pharm Sci. 2014;4(2):74–80. [Google Scholar]
  • 10.Gebremariam A. Factors predisposing to low birth weight in Jimma hospital southwestern Ethiopia. East Afr Med J. 2005;82(11):554–558. doi: 10.4314/eamj.v82i11.9408. [DOI] [PubMed] [Google Scholar]
  • 11.Teklehaimanot N, Hailu T, Assefa H. Prevalence and factors associated with low birth weight in Axum and laelay maichew districts, North Ethiopia: a comparative cross-sectional study. Int J Nutr Food Sci. 2014;3(6):560–566. doi: 10.11648/j.ijnfs.20140306.21. [DOI] [Google Scholar]
  • 12.Tema T. Prevalence and determinants of low birth weight in Jimma Zone, Southwest Ethiopia. East Afr Med J. 2006;83(7):366. doi: 10.4314/eamj.v83i7.9448. [DOI] [PubMed] [Google Scholar]
  • 13.Badshah S, Mason L, McKelvie K, Payne R, Lisboa PJ. Risk factors for low birthweight in the publichospitals at Peshawar, NWFP-Pakistan. BMC Public Health. 2008;8(1):197. doi: 10.1186/1471-2458-8-197. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Central Statistical Agency (CSA) [Ethiopia] and ICF . Ethiopia demographic and health survey 2016. Rockville: CSA and ICF; 2016. p. 2016. [Google Scholar]
  • 15.Benishangul-Gumuz Regional state REDD + design: a regional model for REDD: Ethiopia. 2017. http://www.et.undp.org/content/ethiopia/en/home/library/environment_energy/CommissionedStudy.html. Accessed 7 Feb 2018.
  • 16.Central Statistical Agency (CSA) [Ethiopia] and ICF. Ethiopia demographic and health survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF. https://dhsprogram.com/pubs/pdf/FR328/FR328.pdf. Accessed 21 Feb 2018.
  • 17.Gebremedhin M, Ambaw F, Admassu E, Berhane H. Maternal associated factors of low birth weight: a hospital-based cross-sectional mixed study in Tigray, Northern Ethiopia. BMC Pregnancy Childbirth. 2015;15:222. doi: 10.1186/s12884-015-0658-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wado YD, Afework MF, Hindin MJ. Effects of maternal pregnancy intention, depressive symptoms and social support on risk of low birth weight: a prospective study from southwestern Ethiopia. PLoS ONE. 2014;9(5):e96304. doi: 10.1371/journal.pone.0096304. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Martin J, Hamilton B, Osterman m et al. National Vital Statistics Reports. 2017;66:1. [PubMed]
  • 20.Statistics Canada. Low birthweight newborn in Canada: health fact sheet, 2000 to 2013. http://www150.statcan.gc.ca. Accessed 3 June 2018.
  • 21.Demelash H, Motbainor A, Nigatu D, Gashaw K, Melese A. Risk factors for low birth weight in Bale zone hospitals, South-East Ethiopia: a case–control study. BMC Pregnancy Childbirth. 2015;15(1):264. doi: 10.1186/s12884-015-0677-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Kliegman R, et al. Nelson textbook of pediatrics. 20. Phialdelphia: Elsevier; 2016. [Google Scholar]
  • 23.Zeleke BM, Zelalem M, Mohammed N. Incidence and correlates of low birth weight at a referral hospital in Northwest Ethiopia. Pan Afr Med J. 2012;12(1):4. [PMC free article] [PubMed] [Google Scholar]
  • 24.Guyatt HL, Snow RW. Impact of malaria during pregnancy on low birth weight in sub-Saharan Africa. Clin Microbiol Rev. 2004;17(4):760–769. doi: 10.1128/CMR.17.4.760-769.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Ismail MR, Ordi J, Menendez C, Ventura PJ, Aponte JJ, Kahigwa E, et al. Placental pathology in malaria: a histological, immunohistochemical, and quantitative study. Hum Pathol. 2000;31(1):85–93. doi: 10.1016/S0046-8177(00)80203-8. [DOI] [PubMed] [Google Scholar]
  • 26.Elhassan EM, Abbaker AO, Haggaz AD, Abubaker MS, Adam I. Anaemia and low birth weight in Medani, Hospital Sudan. BMC Res Notes. 2010;3(1):181. doi: 10.1186/1756-0500-3-181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.McClure EM, Goldenberg RL, Dent AE, Meshnick SR. A systematic review of the impact of malaria prevention in pregnancy on low birth weight and maternal anemia. Int J Gynecol Obstet. 2013;121(2):103–109. doi: 10.1016/j.ijgo.2012.12.014. [DOI] [PubMed] [Google Scholar]
  • 28.Muthayya S. Maternal nutrition and low birth weight-what is really important. Indian J Med Res. 2009;130(5):600–608. [PubMed] [Google Scholar]
  • 29.Ismail IM, Venugopalan P. Case-control study on risk factors of low birth weight in a tertiary care hospital, Kerala. Ann Community Health. 2016;4(3):5–12. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data will be available upon request from the corresponding author.


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