Magnitude of Low Birth Weight and Associated Factors Among Newborns Delivered in Public Hospitals of Benadir Region,Somalia: A Facility-Based Cross-Sectional Study

Abstract

Background:

Low birth weight (LBW) is a major global health concern, contributing to 15% to 20% of neonatal mortality, particularly in developing countries like Somalia. Infants with LBW face increased risks of childhood stunting and metabolic disorders. This study assessed the prevalence and associated factors of LBW among newborns in public hospitals in the Benadir region, Somalia.

Methods:

A hospital-based cross-sectional study was conducted in Mogadishu from May 2 to July 19, 2024. Data on newborn and maternal characteristics were collected using a structured questionnaire. Multivariable logistic regression identified significant LBW factors.

Results:

Among 384 newborns, 17.9% had LBW (mean birth weight: 2.76 ± 0.69 kg). Significant risk factors included maternal age, education, residence, ANC visits, anemia, inadequate food intake, short birth interval, low maternal BMI, maternal complications, and lack of iron-folic acid supplementation.

Conclusion:

Strengthening maternal health policies, improving nutrition, and enhancing antenatal care services are essential to reducing LBW in Somalia.

Keywords

low birth weight prevalence risk factors maternal health Somalia

Background

The World Health Organization (WHO) defines low birth weight (LBW) as having a birth weight of less than 2.5 kg regardless of the neonate’s gestational age.¹ The baby’s birth weight is a critical indicator of the population’s general health. LBW infants risk developing cognitive deficiencies, motor delays, cerebral palsy, and emotional issues.^2,3 A baby’s birth weight, in general, is a significant indicator of their health state and a key element in determining how healthy, long-lived, and mentally developed they will be. Furthermore, it provides information on the mother’s current and previous health,^4,5 but in most developing countries, including Somalia, improving birth weight as a strategy of reducing child mortality receives little attention.⁶

According to estimates, 15% to 20% of all births globally, which is more than 21 million births per year, are LBW babies.⁷ The magnitude of LBW varies greatly by region, but evidence suggests that the most vulnerable populations in low- and middle-income nations account for roughly half of all low birth weight cases. LBW is more common in Africa, where it can range from 6.3% to 25.5%.⁸ In Ethiopia, the magnitude of newborn with low birth weight ranged from 7.8% to 54%.^9
-12 The majority of newborn with LBW are born in developing countries, according to the WHO; 90% of these were in sub-Saharan Africa, with Somalia being one of these sub-Saharan countries.¹³

According to Somali Health and demographic Survey 2020, the magnitude of low birth weight was 9%.¹⁴ This is lower than the rate for the Africa region. In the meanwhile, there is inadequate data to evaluate the progress Somalia has made toward meeting the low birth weight target, as well as sufficient prevalence data. A number of studies have identified various factors as determinants of LBW, including a young maternal age at pregnancy, birth sequence, family income, under nutrition, underweight, pregnancy-related complications, preterm birth, chronic illnesses, multiple pregnancies, history of prior LBW, inadequate prenatal care, maternal smoking, maternal anemia, and residence.^15
-18

Reducing the incidence of low birth weight requires a comprehensive global strategy, which must include improving maternal nutritional status; treating pregnancy-associated conditions such as pre-eclampsia (hypertensive disease of pregnancy); and providing adequate maternal care, perinatal clinical services, and social support.⁷

Nevertheless, the Somali Health and Demographic Survey have not investigated factors such as ANC visits, IFA consumption, maternal age, and place of residence. Therefore, this research was aimed to fill this gap and enhance to understanding of the potential risk factors associated with low birth weight in Somali context. The results of this study will contribute valuable local evidence, aiding in informed planning for interventions aimed at addressing the issue of low birth weight.

Methods and Materials

Study Setting, Period and Design

This facility-based cross-sectional study was carried out in 2 specific hospitals within the Benadir region of Somalia between May 2 to July 19, 2024. These hospitals, namely Benadir Hospital and SOS Hospital, were purposefully chosen from the available public hospitals in Mogadishu due to their specialization in maternity and child services.

These hospitals are the primary sources of comprehensive maternity and child care services not only within the Benadir region; but also, for the entire country, functioning as referral hospitals for such specialized care. The study aimed to investigate various aspects of maternity and child care services within these hospitals and the broader regional context.

Study Populations

The source population consisted of all mothers who had attended deliveries at the Benadir and SOS hospitals, while the study population consisted of all mothers who had attended deliveries during the data collection period.

Eligibility Criteria

Mothers who delivered at those hospitals and provided formal consent were considered for inclusion. Exclusions encompassed twin deliveries, cases where the last menstrual period (LMP) was unknown, instances of stillbirths, mothers unable to communicate (such as those with deafness), or those who passed away after childbirth.

Sample Size Determination and Sample Techniques

The sample size was determined using the formula for a single population proportion, considering a 95% confidence level and a margin of error of 3%. The proportion of low birth weight (LBW) was derived from a facility-based study in the Somali Health and Demography Survey, and it was set at 9%. The final sample size after adding 10% non-response rate was 384. The sample size was distributed proportionally among the hospitals. Consecutive sampling was employed to select study participants during the collection period.

Study Variables

Low birth weight, which was <2500 g for neonates, was the dependent variable in this study. The independent variables were socio-demographic includes (Maternal age, education level, marital status and occupational status, family income level and place of residence). Obstetric related factors include; parity, gravidity, utilization of ANC services, birth interval. Nutritional related factors such as anemia, and maternal mid-upper arm circumference.

Data Collection Techniques

Data from the study participants were gathered using a structured questionnaire. Following an extensive assessment of the literature pertinent to our study, the questionnaire was modified. For appropriateness and acceptance in addressing respondents, it was composed in English, translated into Somali, and then translated back into English.

Data Quality Control

Three days were dedicated to teaching data collectors the skill of gathering data. The questionnaire was pre-tested with 5% of the mothers who gave birth in the SOS hospital. The principal investigators were in responsible of daily monitoring the data collectors. Before entering, the data collected was checked for consistency and completeness. Four qualified midwives who worked in the hospital’s labor wards gathered the data. Additionally, all mothers were examined and questioned, and the birth weight of a neonate was determined within an hour of birth using a beam balance scale.

Data Processing and Analysis

The data was entered into an Excel spreadsheet and then exported to SPSS version 22.0 for analysis. Descriptive statistics, including frequency, percentage, mean, and standard deviation, were employed for analysis. Bivariate and multivariate logistic regression analyses were conducted to examine the factors associated with low birth weight. In the final model, variables with a P-value ≤.2 from the bivariate model were incorporated. Variables demonstrating a P-value ≤.05 in the multivariable model were regarded as having a statistically significant association with the LBW. The odds ratio with 95% confidence intervals was reported. Tables were utilized for visual representation of the data, and the goodness of fit for the model was evaluated through the Hosmer lemisho test.

Results

Sociodemographic, Newborn Characteristics of Study Participants

The study included 384 participants, with a 100% response rate. The mean maternal age was 25.3 ± 4.6 years, with more than half (52.1%) being over 25 years old. Most mothers (92.2%) were married, and a significant proportion (69%) had informal education. Unemployment was high, with 91.1% of mothers not working, and 41.7% lived in rural areas. Income was relatively low, with 35.2% earning between $50 and $150 monthly, and most families had fewer than 7 members (75.3%). The gender distribution of newborns favored females (56.5%). The overall prevalence of low birth weight was 17.9% (95% CI: 9.8, 25.7%), with a higher proportion of female neonates (59.5%) being affected (Table 1).

Table 1.

Sociodemographic, Newborn Characteristics of Study Population, 2024 (n = 384).

Variables	Category	Frequency	Percentages
Maternal age (years)	<25	184	47.9
Maternal age (years)	≥25	200	52.1
Gender of newborn	Male	167	43.5
Gender of newborn	Female	217	56.5
Birth weight of baby (kg)	<2.5	69	17.9
Birth weight of baby (kg)	≥2.5	315	82.1
Marital status	Married	354	92.2
	Divorced	28	7.3
	Widowed	2	0.5
Educational level	Informal education	265	69.0
Educational level	Formal education	119	31.0
Occupational status	Unemployed	350	91.1
Occupational status	Employed	34	8.9
Place of residence	Urban	224	58.3
Place of residence	Rural	160	41.7
Family income per month $	<50	109	28.4
	50-150	135	35.2
	150-350	117	30.5
	>350	23	6.0
Family size	<7	289	75.3
Family size	≥7	95	24.7

Obstetric and Nutritional Characteristics of Respondents

The study found that 61.7% of mothers had a parity greater than 5, while the majority (67.4%) had fewer than 5 pregnancies. Regarding maternal complications, over half (53.3%) had a history of pregnancy-related complications, and 32.2% had a history of abortion. Nearly 88% of the mothers had a birth interval of less than 2 years. More than half (52.6%) of the mothers had attended antenatal care (ANC) visits, with 44.3% having at least 3 visits. In terms of delivery method, 70.3% of women had a spontaneous vaginal birth.

Additionally, 13.3% of mothers reported a history of low birth weight in previous pregnancies. Over half of the mothers (56.5%) consumed additional food during pregnancy, and 51% received iron and folic acid supplements during ANC follow-up. However, 47.7% of mothers experienced anemia during their current pregnancy. Most mothers (86.5%) had a normal Mid-Upper Arm Circumference (MUAC), and 77.6% had a Body Mass Index (BMI) within the normal range of 18.5 to 24.9, while 6.7% had a BMI under 18.5 (Table 2).

Table 2.

Obstetric and Nutritional Characteristic of Respondents, 2024 (n = 384).

Variables	Category	Frequency	Percentages
Parity	<5 children	67	17.4
Parity	≥5 children	237	61.6
Gravidity	<5	259	67.4
Gravidity	≥5	125	32.6
Complication experience during pregnancy	Yes	205	53.3
Complication experience during pregnancy	No	179	46.7
History of abortion	Yes	124	32.3
History of abortion	No	260	67.7
Birth interval (in years)	≤2	338	88.0
Birth interval (in years)	>2	46	12.0
ANC visit	Yes	202	52.6
ANC visit	No	182	47.4
Number of ANC visit (N = 202)	≤3 visits	170	93.4
Number of ANC visit (N = 202)	>3 visits	32	6.6
Types of delivery	Vaginal	271	70.3
Types of delivery	Cesarean section	113	29.4
History of low birth weight	Yes	51	13.3
History of low birth weight	No	333	86.7
Did you take additional food during pregnancy	Yes	217	56.5
Did you take additional food during pregnancy	No	167	43.5
Any prenatal supplements for iron or folic acid	Yes	196	51.0
Any prenatal supplements for iron or folic acid	No	188	49.0
Anemia status	Yes	183	47.7
Anemia status	No	201	52.3
What is the mid-upper arm circumference (MUAC)	<23	52	13.5
What is the mid-upper arm circumference (MUAC)	≥23	332	86.5
BMI for mothers (in kg/m²)	<18.5	26	6.7
	18.5-24.99	298	77.6
	≥25	60	15.6

Determinants of Low Birth Weight Among Newborns

The study found that maternal age and place of residence significantly influenced the occurrence of low birth weight (LBW). Mothers under 25 years had a 1.9 times higher likelihood of giving birth to LBW babies compared to those over 25 years (AOR = 1.9, 95% CI = 1.14-3.25, P = .039). Additionally, mothers residing in rural areas had nearly twice the risk of having LBW babies compared to those in urban areas. Maternal education also played a role, with uneducated mothers having a 2.3 times higher risk of delivering LBW babies compared to those with formal education (AOR = 2.3; 95% CI = 1.21-4.37, P = .022). However, maternal occupation, family income, and newborn gender were not found to be significantly associated with LBW.

Several obstetric and nutritional factors were also significant. Mothers who had complications during their pregnancy were 1.86 times more likely to deliver a LBW baby (AOR = 1.86, 95% CI = 1.06-3.11, P = .030). Birth intervals of less than 2 years were associated with a 2.7 times increased risk of LBW (AOR = 2.7, 95% CI = 1.98-8.19, P = .0001). Women who did not receive antenatal care (ANC) had a 4.11 times higher chance of delivering a LBW baby (AOR = 4.11, 95% CI = 2.21-7.61, P = .0001). In contrast, mothers who did not consume additional food during pregnancy had a 1.57 times greater likelihood of giving birth to a LBW baby (AOR = 1.57, 95% CI = 1.33-2.79, P = .021). Mothers with anemia during pregnancy had more than a threefold increased risk of delivering LBW babies (AOR = 3.12, 95% CI = 1.70-6.07, P = .0001). Additionally, mothers with a BMI of less than 18.5 kg/m² had a 9.12 times higher likelihood of giving birth to a LBW baby compared to those with a higher BMI (Table 3).

Table 3.

Bivariate and Multivariate Logistic Regression Analysis of Associated Factors with Low Birth Weight Among Newborns, 2024 (n = 384).

Variables	Category	Low birth weight		COR (95%CI)	AOR (95% CI)	P-value
Variables	Category	Yes %	No %	COR (95%CI)	AOR (95% CI)	P-value
Maternal age (years)	<25	45 (65.2)	139 (44.1)	2.3 (1.37-4.08)	1.9 (1.14-3.25)	.039*
Maternal age (years)	≥25	24 (34.8)	176 (55.9)	1	1
Maternal education	Informal education	58 (84.1)	207 (65.7)	2.7 (1.38-5.45)	2.3 (1.21-4.37)	.022*
Maternal education	Formal education	11 (15.9)	108 (34.3)	1	1
Current occupation	Unemployed	67 (97.1)	283 (89.8)	0.26 (0.06-1.12)	2.89 (0.63-13.14)	.169
Current occupation	Employed	2 (2.9)	32 (10.2)	1	1
Place of residence	Urban	31 (44.9)	193 (61.3)	1	1
Place of residence	Rural	38 (55.1)	122 (38.7)	1.93 (1.14.3.24)	1.77 (1.01-3.91)	.014*
Family income ($)	<150	51 (73.9)	193 (61.3)	1.8 (0.99-3.21)	1.0 (0.46-2.09)	.980
Family income ($)	≥150	18 (26.1)	122 (38.7)	1	1
Complication experience	Yes	45 (65.2)	160 (50.7)	2.0 (1.05-3.12)	1.86 (1.06-3.11)	.030*
Complication experience	No	24 (34.8)	155 (49.3)	1
Birth interval (years)	<2	66 (95.7)	272 (86.3)	3.4 (1.04-11.55)	2.7 (1.98-8.19)	.012*
Birth interval (years)	≥2	3 (4.3)	43 (13.7)	1	1
ANC visit	Yes	17 (24.6)	185 (58.7)	1	1
ANC visit	No	52 (75.4)	130 (41.3)	4.3 (2.40-7.87)	4.11 (2.21-7.61)	<.0001*
Additional food during pregnancy	Yes	30 (43.5)	187 (59.4)	1	1
Additional food during pregnancy	No	39 (56.5)	128 (40.6)	1.89 (1.12-3.21)	1.57 (1.33-2.79)	.021*
Supplements for IFA	Yes	12 (17.4)	184 (58.4)	1	1
Supplements for IFA	No	57 (82.9)	131 (41.9)	0.15(0.07-0.29)	6.26 (3.07-12.71)	<.0001*
Maternal anemia	Yes	48 (69.6)	135 (42.9)	1	1
Maternal anemia	No	21 (30.4)	180 (57.1)	3.04 (1.74-5.33)	3.12 (1.70-6.07)	<.0001*
Maternal BMI (kg/m²)	<18.5	17 (24.6)	9 (2.9)	11.1 (4.70-26.26)	9.12 (4.13-24.05)	<.0001*
Maternal BMI (kg/m²)	≥18.5	52 (75.4)	306 (97.1)	1	1

Abbreviations: IFA, iron and folic acid; BMI, body mass index; ANC, antenatal care; OR, odds ratio; CI, confidence interval.

Statistically significant P ≤ .05.

Discussion

This study found a magnitude of low birth weight of 17.9%, which is consistent with research done in Ethiopia.¹⁹ But it’s much higher than the estimate of LBW from the Somalia Health and demographic survey 2020 (9%).²⁰ It is difficult to contrast this finding to SHDs, which are determined by maternal reports rather than measurements. This high magnitude of low birth weight in this study is a clear implication that there is a need for aggressive prevention of low birth weight among pregnant women. The observed variation may be linked to the study setting, given that the research was conducted in a referral maternal hospital. Additionally, these hospitals are conveniently located in the town center, facilitating easy accessibility for mothers.

The magnitude of LBW in this study was greater than studies on birth weight carried out in several regions of Ethiopia, such as Wolaita Sodo and Adwa general hospital, where the frequency of LBW was discovered to be 8.1% and 10%, respectively^21,22 There are several possible explanations for this, the first of which is that most pregnant women in the country do not obtain antenatal care due to the poor healthcare system. Secondly, many pregnant women do not receive proper nutrition due to poor economic profile and differences in pregnant women’s nutritional status and the healthcare provider’s dedication to providing ANC services, which results in the delivery of newborns with low birth weights. Additionally, another aspect that could be the reason for this inconsistency is the time variation between the studies. The study conducted in Adwa General Hospital in Northern Ethiopia was conducted 7 years prior to the current study. Improvement in healthcare availability and quality over time may lead to a reduction in low birth weight rates. Somalia, which has been profoundly affected by prolonged civil conflict, has experienced significant disruptions to its healthcare infrastructure. These disruptions have impaired the delivery of essential services, particularly maternal care, contributing to adverse perinatal outcomes such as the increased magnitude of low birth weight.

In the present study, the magnitude of low birth weight in this study is lower than the study conducted in Kersa, Ethiopia (28.3%)²³ and Assam, India.²⁴ This discrepancy may be due to differences in study settings and designs. For instance, the Ethiopian study was a cohort study, which typically requires a much larger sample size than other study designs. And although the Indian study was conducted in a community setting, this one was conducted specifically in hospitals and other healthcare facilities. It is assumed that women who gave delivery in medical facilities received prompt ANC follow-up and effective interventions, which dramatically lower low birth weight.^18
-25

This study revealed a wide variety of sociodemographic, obstetric, and maternal nutrition factors associated with low birth weights. Regarding socio-demographic factors, it has been found that the maternal age, place of residence. The study has shown that mothers less the age of 25 were 1.9 times more likely than mothers who were over the age of 25 to give birth to babies with low birth weight, this is an agreement study done in Nepal.²⁶ The mother’s place of residence was a risk factor for low birth weight; the mother’s place of residence was statistically associated with low birth weight; mothers in rural areas were 1.93 times more likely than mothers in urban areas to give birth to babies with low birth weight (AOR = 1.93; 95% CI = 0.57-1.76, P = .982), which is similar to study conducted in Tanzania²⁷ and India.²⁸ However, this result is in contrast to a study carried out in Jimma Zone, Ethiopia.²⁹ The variation may be due to mothers in rural areas constantly working and getting not enough rest during their pregnancies.

Mothers without formal education had a 2.3 times higher likelihood of giving birth babies with LBW compared to mothers with formal education (AOR = 2.3; 95% CI = 1.21-4.37, P = .022). Similarly to this, a study done in Nepal found that maternal education was significantly associated with LBW.³⁰ The possible explanation could be, the mothers who are educated had a good perception of the benefit of utilization of health care services. However, this study revealed no statistically significant between maternal occupational status and LBW which is different from other previous study findings.^27
-30 This finding complements a prior study conducted in Tanzania, which found no statistically significant association between maternal occupation and low birth weight.²⁷

Regarding obstetric and maternal nutrition factors, the study revealed that the mother’s birth interval were associated with low birth weight, mothers with birth intervals less than 2 years had a 3.4 times higher likelihood of delivering a baby who was LBW compared to mothers with birth intervals over 2 years (AOR = 3.4; 95% CI = 1.02-11.55, P < .001), which is an agreement the studies conducted in India and Iran that showed birth interval of less than 2 years were at higher probability to deliver LBW baby.^31,32 This may be because a short time interval between pregnancies leads to the insufficient restoration of the maternal nutrient reserves depleted during the previous pregnancy, which in turn causes a reduction in fetal growth.

We also found that the mothers with experience complications related to pregnancy were associated with low birth weight, which is in line with the study conducted in Ethiopia.³³ Interestingly, ANC visit had a significant association with LBW. The odds of having a baby with low birth weight were 4.3 times higher among women who never received ANC services. This is similar with a prior study conducted in Nepal that revealed an association between birth weight and the use of antenatal services.²⁸ Antenatal visits for pregnant women are crucial because they give the opportunity to check on the fetus’ health and enable immediate action for feta-maternal protection, such as the dietary advice a mother might obtain. The Somali Health Demographic Survey emphasized the necessity for additional interventions in the care sought by women before and after childbirth, aiming to assist both women and their caregivers in making informed decisions. Specifically, the survey revealed that only 31% of women aged 15 to 49, who had a live birth, received Antenatal Care (ANC) from skilled personnel during their last childbirth. Furthermore, this study found that a mere 41% of mothers attended antenatal care services during their last pregnancy, indicating a need for heightened awareness to boost attendance of ANC services.²⁰

Regarding the association between a mother’s nutritional factors and low birth weight, the study discovered that the likelihood of giving birth to a baby with LBW was more than 1.57 times higher in mothers who did not consume additional foods during pregnancy than in mothers who did (AOR = 1.57; 95% CI = 1.33-2.79, P = .021). Similarly, the study conducted in Ethiopia.³⁴ In fact, receiving nutritional counseling and eating a sufficient and balanced diet throughout pregnancy had a good effect on both the mother’s and the fetus’s weight. Furthermore, maternal nutritional status has a significant impact on healthy and optimum intrauterine fetal growth.³⁴

As per this study, our study reviled that the odds of being LBW in newborn from mothers who had anemia during their current pregnancy were found to have a great chance of delivering a low birth weight baby as compared with mothers who had no anemia, consistent with a study in Yemen.³⁵ Pregnancy-related micronutrient deficiencies have been associated with substantial consequences for the growing fetus and consequently birth weight. The fetus’s normal intrauterine growth may be hampered by severe anemia, which would reduce oxygen delivery. Ultimately, our study showed that there was an association between maternal BMI and LBW, with women with a BMI of less than 18.5 kg/m² having a higher likelihood of giving birth to babies with low birth weight. Studies were undertaken elsewhere and these are in agreement.^36,37 The novelty of this study lies in its exploration of the increase in low birth weight occurrences in the Benadir region, in contrast to the Somali Health and Demography Survey last reported in 2020. Furthermore, the study identifies several factors associated with low birth weight that were not revealed in the Somali Health and Demographic Survey.

Conclusion

Low birth weight (LBW) remains a pressing public health challenge, with a prevalence of 17.9%, exceeding the estimate from the 2020 Somali Health, and Demographic Survey. Several maternal factors, including age, education, place of residence, antenatal care (ANC) visits, birth interval, nutritional intake, supplement use, anemia, and pregnancy complications, were found to be significantly associated with LBW.

To address this issue, a multi-faceted approach is essential. Strengthening nutrition education during ANC visits can help prevent maternal malnutrition, ensuring women receive guidance on balanced diets and essential nutrient intake. Additionally, community-based nutritional support programs should be implemented, particularly in underserved and disadvantaged populations. These programs should focus on increasing access to micronutrient supplements, fortified foods, and dietary counseling to improve maternal health and birth outcomes.

Moreover, expanding ANC services, promoting maternal health awareness, and addressing socio-economic barriers to proper nutrition are critical steps in reducing LBW prevalence. A collaborative effort between healthcare providers, policymakers, and community organizations is necessary to implement sustainable interventions that improve maternal and neonatal health outcomes.

Footnotes

Acknowledgements

The management of the Benadir and SOS Hospitals provided support and collaboration, and also center for research development- SIMAD University which the authors gratefully acknowledge.

ORCID iD

Jamal Hassan Mohamoud

Statements and Declarations

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