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. 2026 Jul 7;21(7):e0347187. doi: 10.1371/journal.pone.0347187

Prevalence of undernutrition and its associated factors among pregnant women attending antenatal care service in public hospitals in Mogadishu, Somalia

Abdullahi Ahmed Tahlil 1,2,3,*, Naimo Abdikadir Abdillahi 4, Asho Jama Adam 4, Anisa Abdi Ali 4, Fadumo Mohumed Ahmed 4, Zeynab Osman Abdi 4, Maryan Muhudin Ali 4, Muno Abdulle Hubur 4, Hassan Ibrahim Nor 3, Mohamed Abdelrahman Mohamed 1, Liban Abdi Ali 1, Osman Mohamed Mohamud 3
Editor: Olutosin Ademola Otekunrin5
PMCID: PMC13340802  PMID: 42412777

Abstract

Introduction

Maternal undernutrition remains a major public health concern globally, particularly in Somalia, where conflict, poverty, and food insecurity exacerbate nutritional deficiencies. Undernutrition during pregnancy poses serious risks to both maternal and fetal health, including increased maternal mortality, low birth weight, and adverse developmental outcomes. Despite its critical implications, there is limited evidence on the burden and associated factors of maternal undernutrition in Somalia. This study assessed the prevalence and associated factors of undernutrition among pregnant women attending antenatal care (ANC) services in public hospitals in Mogadishu.

Methods

A facility-based cross-sectional study was conducted among 734 pregnant women attending antenatal care (ANC) services in public hospitals in Mogadishu. Participants were selected using a multistage sampling technique. Data were collected using interviewer-administered questionnaires and anthropometric measurements. Undernutrition was assessed using mid-upper arm circumference (MUAC < 23 cm), a measure commonly applied in clinical and humanitarian settings. Household food insecurity was assessed using the Household Food Insecurity Access Scale (HFIAS). Data were analyzed using SPSS version 26, and multivariable logistic regression was performed to identify factors associated with undernutrition at a significance level of p < 0.05.

Results

The prevalence of maternal undernutrition was 75.7% (95% CI: 72.6%–78.9%). Factors independently associated with undernutrition included maternal age 25–31 years (AOR = 2.61, 95% CI: 1.28–5.30) and 32–38 years (AOR = 2.18, 95% CI: 1.04–4.55), tertiary education (AOR = 3.43, 95% CI: 1.89–6.21), employee occupation (AOR = 6.38, 95% CI: 2.90–14.04), private business occupation (AOR = 9.79, 95% CI: 4.27–22.43), large household size (AOR = 1.96, 95% CI: 1.34–2.88), urban residence (AOR = 2.40, 95% CI: 1.39–4.15), household monthly income < USD 500 (AOR = 1.98, 95% CI: 1.33–2.94), lack of latrine facility (AOR = 2.00, 95% CI: 1.23–3.26), second (AOR = 8.59, 95% CI: 5.29–13.97) and third trimester (AOR = 6.91, 95% CI: 2.97–16.08), primigravidity (AOR = 2.29, 95% CI: 1.52–3.45), contraceptive use (AOR = 1.98, 95% CI: 1.34–2.90), substance use (AOR = 2.79, 95% CI: 1.93–4.04), and severe household food insecurity (AOR = 1.76, 95% CI: 1.01–3.08). However, some associations with large effect sizes should be interpreted with caution, as they may reflect residual confounding, small subgroup sizes, or model instability.

Conclusion

This study revealed a high prevalence of maternal undernutrition among pregnant women attending ANC services in Mogadishu, with multiple factors found to be associated with undernutrition. These findings highlight the need for targeted, multi-sectoral interventions to improve maternal nutrition through enhanced food security, health education, and access to nutrition-sensitive and nutrition-specific services. Targeted strategies such as supplementation programs, nutrition counseling, and improved water, sanitation, and hygiene (WASH) services are critical to mitigating maternal undernutrition and achieving Sustainable Development Goals related to maternal and child health.

Introduction

Undernutrition among pregnant women remains a significant public health challenge worldwide, particularly in low- and middle-income countries such as Somalia, where socioeconomic disparities, limited healthcare access, and food insecurity are prevalent [1]. It is recognized as one of the top ten risk factors contributing to the global burden of disease [2]. The World Health Organization (WHO) defines undernutrition as a condition resulting from inadequate nutrient intake, poor absorption or utilization, or excessive nutrient losses, which lead to harmful health consequences [3]. Undernutrition in pregnant women, characterized by a BMI of less than 18.5 kg/m² and/or a MUAC of less than 23 cm, results from insufficient intake of essential nutrients, leading to low maternal weight gain, anemia, and other deficiencies that increase the risk of adverse outcomes such as preterm birth, low birth weight, and maternal mortality [4,5]. Women are particularly vulnerable to undernutrition due to increased physiological demands during menstruation, pregnancy, childbirth, and lactation [6]. During pregnancy and lactation, women’s nutritional requirements for energy, protein, and micronutrients are significantly elevated to support maternal health and fetal development [7].

Globally, more than one billion adolescent girls and women suffer from undernutrition, including deficiencies in essential micronutrients such as iron, folate, and vitamin A. These deficiencies exacerbate risks during pregnancy and childbirth, contributing to approximately 20 million infants being born annually with low birth weight, an early form of malnutrition; over half of these low-birth-weight births occur in South Asia, and about a quarter in Africa [8,9]. Maternal malnutrition is responsible for approximately 7% of the overall disease burden and contributes to at least a fifth of maternal mortality, with a particularly significant impact on adverse pregnancy outcomes [10]. Maternal undernutrition is associated with intrauterine growth restriction (IUGR), low birth weight, preterm birth, and increased neonatal mortality, accounting for nearly 45% of under-five deaths linked to malnutrition [11]. According to the Global Nutrition Report (2018), approximately 38% of pregnant women globally are anemic, primarily due to iron deficiency, which is a key indicator of undernutrition during pregnancy [12]. Undernutrition is a multifaceted issue influenced by inadequate dietary intake, infectious diseases, poor sanitation, and limited access to healthcare services. These factors are compounded by poverty, food insecurity, lower educational attainment, and cultural practices that influence dietary behaviors during pregnancy [13,14]. These consequences contribute substantially to the global burden of maternal and child morbidity and mortality, particularly in low- and middle-income countries (LMICs), where the prevalence of undernutrition among pregnant women tends to be higher than in developed nations [15].

In Africa, the prevalence of undernutrition among pregnant women remains alarmingly high, with approximately 34.8% of women of reproductive age in sub-Saharan Africa being undernourished, with nutritional deficiencies contributing to nearly 20% of maternal deaths in the region [13,16]. The prevalence among pregnant women is often higher due to compounded factors such as food insecurity, poverty, limited access to quality healthcare, inadequate nutritional education, and sociocultural practices that influence dietary habits [17]. These determinants are further intensified in fragile settings characterized by conflict, displacement, and recurrent emergencies, which disrupt food systems and healthcare delivery.

In Somalia, a country grappling with prolonged conflict, recurrent droughts, and fragile health systems, the maternal mortality rate is one of the highest globally, at 692 deaths per 100,000 live births, with malnutrition being a leading indirect cause [18,19]. According to the Somali Health and Demographic Survey 2020, approximately 15% of pregnant women in Somalia experience undernutrition [20]. It is important to note that national estimates, such as those reported in the Somali Health and Demographic Survey (SHDS 2020), are primarily based on body mass index (BMI), which reflects chronic nutritional status and may not adequately capture acute changes in maternal nutritional status during pregnancy. In contrast, the present study uses mid-upper arm circumference (MUAC), which is more sensitive to acute undernutrition and is widely recommended in clinical and humanitarian settings for its simplicity and reliability. These methodological differences are critical and should be considered when interpreting and comparing prevalence estimates across studies. Similarly, only 31% of pregnant women receive antenatal care (ANC) from skilled providers, and a mere 24% complete the WHO-recommended four ANC visits, limiting early detection and management of nutritional deficiencies [20]. Recent studies in Mogadishu indicate alarming rates of anemia (69%) among pregnant women, driven by factors such as early marriage (<16 years), low household income (<$100/month), inadequate iron supplementation, and poor dietary practices, including infrequent meat consumption and tea intake, which inhibits iron absorption [21]. Additionally, food insecurity affects over 24.5% of households, severely restricting access to diverse, nutrient-rich diets essential for maternal and fetal health [22].

Although the SHDS 2020 reported a high prevalence of malnutrition among pregnant women in Somalia, this estimate was derived from a nationally representative household survey that relied primarily on body mass index (BMI) and did not focus on urban humanitarian settings or facility-based populations. In contrast, the present study specifically assessed acute maternal undernutrition using mid-upper arm circumference (MUAC < 23 cm) among pregnant women attending antenatal care services in public hospitals in Mogadishu, a city characterized by prolonged conflict, mass internal displacement, and severe urban poverty. Pregnant women attending antenatal care services in Mogadishu represent a particularly high-risk subgroup, as many reside in urban poor settings characterized by overcrowding, food insecurity, and limited access to stable income and nutritious foods. Additionally, Mogadishu hosts a large population of internally displaced persons (IDPs), who are disproportionately affected by acute malnutrition and rely heavily on public health facilities for essential maternal care.

Furthermore, existing studies in Somalia have largely concentrated on anemia or child malnutrition, with limited facility-based evidence focusing on maternal undernutrition during pregnancy, particularly using MUAC as a screening tool. MUAC is more sensitive to short-term nutritional stress and is recommended in emergency and humanitarian contexts where rapid assessment is required. Existing studies in Somalia have primarily focused on anemia or child malnutrition. This study, therefore, aims to assess the prevalence of undernutrition and its associated factors among pregnant women attending ANC services at public hospitals in Mogadishu, Somalia. The findings will contribute to the sparse body of evidence on maternal nutrition in Somalia and support policymakers in designing effective strategies to mitigate undernutrition. Addressing this gap is critical to achieving Sustainable Development Goals (SDGs) 2 (Zero Hunger) and 3 (Good Health and Well-being), particularly in a setting where maternal and child survival depend on equitable access to nutrition and healthcare services. This study provides context-specific, clinically relevant evidence that complements national survey findings and addresses an important evidence gap regarding maternal undernutrition in Mogadishu’s urban and displaced populations.

Methods and materials

Study design and settings

This study employed a facility-based cross-sectional design to determine the prevalence of undernutrition and its associated factors among pregnant women attending antenatal care (ANC) services. The study was conducted in Mogadishu, Somalia, which is the largest city and the country’s capital. It is located in the coastal region of Banadir in the Horn of Africa and is home to more than 2.7 million residents. Mogadishu is bordered by the regions of Middle Shebelle and Lower Shebelle, as well as the Indian Ocean, and consists of 20 districts.

This study was conducted in selected public hospitals in Mogadishu, including Benadir, Demartino, and SOS hospitals. Benadir Hospital serves as a public teaching hospital, a mother-and-child hospital, and a nationwide referral hospital. It was built in 1976 and has a capacity of approximately 550–700 beds, managed by the Federal Ministry of Health (FMOH). Demartino Hospital is a public referral hospital serving the most vulnerable populations, including pregnant women and children. It was established in 1922 and has a capacity of more than 280 beds. It is also managed by the FMOH. SOS Hospital is a non-governmental hospital administered by SOS Children’s Villages International and focuses on child and maternal health. It was opened in 1989 and has a capacity of approximately 150 beds. This selected hospital serves as the primary point of ANC service delivery for a diverse population of pregnant women in the region. The hospital conducts approximately 1,200 deliveries per month, highlighting its critical role in maternal health in the region.

Study period and population

Data collection and participant recruitment were carried out from 25/04/2025–29/05/2025. The target population comprised all pregnant women aged 18–49 years attending ANC clinics at the selected public hospitals during the study period. Inclusion criteria included women who were in any trimester of pregnancy, attending routine ANC visits, and willing to participate in the study after providing informed consent. Women with critical medical conditions, severe disabilities, or conditions that could interfere with anthropometric measurements or data collection were excluded to ensure the accuracy and reliability of the data collected.

Sample size and sampling procedure

Sample size determination was calculated based on the single proportion formula:n = Z2 × p×(1-p)/d2, where: n is the required sample size, Z is the Z-score corresponding to the desired 1.96 for a 95% confidence level, p is the estimated proportion of the attribute in the population, q is 1 − p, and d is the margin of error. Considering an anticipated prevalence of undernutrition of 39.2% from previous studies in Ethiopia [23], a 95% confidence level, a 3.7% margin of error, and accounting for a non-response rate of 10%. Using these values in the formula: n = (1.96)2 * 0.392 * (1-0.392) / (0.037)2 = 670. To account for a potential non-respondent rate of 10%, the final sample size was calculated using the following formula: n / (1 – non-respondents’ rate) = 670 / (1 - 0.1) = 744. Therefore, the final sample size for this study, after accounting for potential non-respondents, was 744 participants.

A multi-stage sampling technique was employed to select participants. First, a list of public hospitals offering antenatal care services in Mogadishu was compiled. From this list, three hospitals were randomly selected. Subsequently, a systematic sampling method was used to select participants. Every kth eligible woman attending the ANC clinic was approached after a random starting point to ensure fairness and representativeness. The sampling interval (k) was determined by dividing the estimated total number of ANC attendees during the data collection period by the allocated sample size for each hospital. For example, if an estimated 1,200 pregnant women attended ANC services during the study period and the allocated sample size for a given hospital was 300, the sampling interval (k) was calculated as 1,200/300 = 4. In this case, every fourth eligible woman was selected after a random starting point. A random number between 1 and k was selected as the starting point, and subsequent participants were chosen by adding k to the initial number until the desired sample size was reached, proportionally across the hospitals and shifts.

Data collection instruments and procedures

Data collection involved two main components: interviewer-administered questionnaires and anthropometric measurements. Data were collected using a structured questionnaire adapted from previous studies [23,24]. The questionnaire was developed in English, then translated into Somali, and subsequently back-translated by a bilingual expert to ensure accuracy. The questionnaire includes sections on socio-demographic characteristics, obstetric history, medical history, Household Food Insecurity Access Scale (HFIAS), 24-hour dietary recall, and anthropometric measurements. Socio-demographic information and obstetric and medical histories captured data on age, education level, occupation, marital status, gravidity, parity, and medical history.

Household food insecurity was assessed using the Household Food Insecurity Access Scale (HFIAS) developed by the Food and Nutrition Technical Assistance (FANTA) project [25]. The HFIAS consists of nine standardized occurrence questions that capture three domains of food insecurity: anxiety about food supply, insufficient food quality, and insufficient food intake over the previous four weeks. Each occurrence question is followed by a frequency-of-occurrence response categorized as rarely (1–2 times), sometimes (3–10 times), or often (>10 times). Households were categorized into four levels: food secure, mildly food insecure, moderately food insecure, and severely food insecure according to standard HFIAS guidelines.

Dietary diversity was assessed using a 24-hour dietary recall method [26]. Participants were asked to recall all foods and beverages consumed in the previous 24 hours, and the reported items were categorized into the ten standard food groups defined by the Minimum Dietary Diversity for Women (MDD-W) indicator. These food groups include: (1) grains, white roots and tubers, and plantains; (2) pulses (beans, peas, and lentils); (3) nuts and seeds; (4) dairy products; (5) meat, poultry, and fish; (6) eggs; (7) dark green leafy vegetables; (8) vitamin A-rich fruits and vegetables; (9) other vegetables; and (10) other fruits. A Dietary Diversity Score (DDS) was calculated for each participant by summing the number of food groups consumed, with scores ranging from 0 to 10. Following established guidelines, women who consumed foods from more than five food groups were classified as having adequate dietary diversity, while those consuming five and fewer food groups were considered to have inadequate dietary diversity [27]. This approach provides a standardized proxy measure of micronutrient adequacy and distinguishes dietary diversity (the number of food groups consumed) from food variety (the number of individual food items consumed), thereby ensuring a more accurate assessment of overall diet quality among pregnant women.

Anthropometric measurements were conducted following WHO guidelines. Height was measured using a portable stadiometer to the nearest 0.1 cm, with participants standing upright without shoes, heels together, and looking straight ahead. Weight was measured using a calibrated digital scale to the nearest 0.1 kg, with participants wearing light clothing and without shoes. Mid-Upper Arm Circumference (MUAC) was measured using a non-stretchable measuring tape. The measurement was taken at the midpoint between the acromion process and the olecranon process on the left arm, with the arm relaxed and hanging freely. The tape was snug but did not compress the tissues. The measurement was recorded to the nearest 0.1 cm. Undernutrition was defined using a MUAC cutoff of <23 cm, consistent with World Health Organization (WHO) and emergency nutrition guidelines, which recommend this threshold for identifying maternal undernutrition in resource-limited and humanitarian settings [28]. MUAC is considered a practical and reliable indicator of acute nutritional status during pregnancy, particularly in contexts where body mass index (BMI) measurement may be less feasible or reliable.

All measurements were performed twice, and the average value was used for analysis to enhance reliability. Measurements were conducted in a private setting to ensure confidentiality and participant comfort. Data collection was carried out by seven trained research assistants at selected public hospitals. Prior to data collection, the research assistants received training in administering questionnaires, taking anthropometric measurements, and ensuring ethical treatment of participants. Each participant was informed about the study’s purpose and procedures, and written informed consent was obtained before data collection.

Data quality control

To ensure data quality, the questionnaire was pre-tested on 5% of the sample size in a comparable setting outside the study area, and necessary modifications were made. Data collectors received a two-day training on study objectives, interview techniques, anthropometric measurements, and ethical considerations. Supervisors regularly monitored data collection processes, checked the completeness and consistency of the data, and provided ongoing support. Double data entry was performed to minimize entry errors, and data cleaning was conducted before analysis.

Data analysis

Data were entered and cleaned into IBM SPSS Version 26. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize the sociodemographic characteristics and nutritional status of the participants. The prevalence of undernutrition was determined based on MUAC thresholds as per WHO criteria. Bivariate analysis was conducted to identify potential factors associated with undernutrition using chi-square tests. Variables were selected for inclusion in the multivariable logistic regression model based on both statistical and theoretical considerations. Specifically, variables with a p-value <0.25 in the bivariate analysis were included, along with variables identified as important predictors of undernutrition. The use of a p-value threshold of <0.25 at the bivariate stage is a commonly applied approach to ensure that potentially important variables are not prematurely excluded from the multivariable model. The model’s goodness-of-fit was evaluated using the Hosmer-Lemeshow test. Multicollinearity among independent variables was assessed using variance inflation factors (VIF), with a VIF value greater than 10 considered indicative of significant multicollinearity. No variables exceeded this threshold, and all were retained in the final model. Adjusted odds ratios (AORs) with 95% confidence intervals (CI) were reported, and statistical significance was set at p < 0.05.

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of the Research and Innovation Center of Zamzam University of Science and Technology [Ref: ZUST/RIC/IRB/008/April/2025]. Permission to conduct the study was secured from the administrative authorities of the selected hospitals. Written informed consent was obtained from all participants after they were fully informed about the study objectives, procedures, potential risks, and benefits. Confidentiality and anonymity were strictly maintained throughout the study. Participation was entirely voluntary, and respondents were assured of their right to withdraw at any stage without repercussions.

Results

Socio-demographic characteristics of the participants

Out of the eligible participants, a total of 734 pregnant women successfully participated in the study, yielding a response rate of 98.7%. The mean age of the participants was 29.3 ± 6.7 years, ranging from 18 to 47 years. The majority, 259 (35.3%), were aged 25–31 years. Most participants, 487 (66.3%), were married. More than half, 398 (54.2%), had no formal education. Regarding occupation, 457 (62.3%) were housewives. A larger proportion, 436 (59.4%), belonged to households with more than seven members. The majority, 591 (80.5%), resided in urban areas, and 470 (64.0%) reported a household monthly income of less than 500 USD. More than half, 447 (60.9%), had at least one child under five years old in the household. Most households, 606 (82.6%), had access to safe drinking water, and 653 (89.0%) had latrine facilities. (Table 1)

Table 1. Socio-demographic Characteristics of Pregnant Women Attending Antenatal Care in Public Hospitals in Mogadishu, Somalia (n = 734).

Variables Frequency Percentage
Age (In Years)
18–24 183 24.9
25–31 259 35.3
32–38 195 26.6
≥ 39 97 13.2
Marital Status
Married 487 66.3
Widowed 64 8.7
Divorced 183 24.9
Educational Level
No formal 398 54.2
Primary 176 24.0
Secondary 107 14.6
Tertiary 53 7.2
Occupation
Daily Laborer 85 11.6
Employee 115 15.7
Housewife 457 62.3
Private Business 77 10.5
Family Size
≤ 7 298 40.6
> 7 436 59.4
Residence
Rural 143 19.5
Urban 591 80.5
Household Monthly Income (In USD)
< 500 470 64.0
≥ 500 264 36.0
Presence of under-five children in the Household
No 287 39.1
Yes 447 60.9
Source of Drinking Water
Safe 606 82.6
Unsafe 128 17.4
Availability of the Latrine facility
No 81 11.0
Yes 653 89.0

Reproductive and medical characteristics of the participants

More than half of the participants, 380 (51.8%), were married before the age of 18. Most women, 616 (83.9%), were in their first trimester of pregnancy at the time of the survey. The majority were multigravida, 542 (73.8%), and multiparous, 658 (89.6%). More than half, 430 (58.6%), had a birth interval of ≤2 years, while 600 (81.7%) reported that the current pregnancy was intended. Regarding antenatal care (ANC), 288 (39.2%) attended two visits, while only 86 (11.7%) had four or more visits. About 471 (64.2%) of the participants reported previous contraceptive use, and 447 (60.9%) received nutritional advice during ANC. More than half reported iron and folic acid supplementation, 402 (54.8%), and deworming, 400 (54.5%). A significant proportion, 451 (61.4%), had a history of previous pregnancy-related complications, while 426 (58.0%) reported current illness. Additionally, 403 (54.9%) experienced frequent illness, and 352 (48.0%) had a chronic illness. About one-quarter, 196 (26.7%), admitted to substance use (Table 2).

Table 2. Reproductive and Medical Characteristics of Pregnant Women Attending Antenatal Care in Public Hospitals in Mogadishu, Somalia (n = 734).

Variables Frequency Percentage
Age at first marriage
< 18 380 51.8
≥ 18 354 48.2
Trimester of pregnancy
First 616 83.9
Second 93 12.7
Third 25 3.4
Gravida (Number of Pregnancies)
Primigravida 192 26.2
Multigravida 542 73.8
Parity (Number of Births)
Primiparous 76 10.4
Multiparous 658 89.6
Birth Interval
≤ 2 years 430 58.6
> 2 years 304 41.4
Intention of the current pregnancy
No 134 18.3
Yes 600 81.7
Number of ANC Visits
1 time 229 31.2
2 times 288 39.2
3 times 131 17.8
≥ 4 times 86 11.7
Previous Contraceptive Use
No 263 35.8
Yes 471 64.2
Nutrition Advice during a Pregnancy Visit
No 287 39.1
Yes 447 60.9
Use of Iron and Folic Acid Supplementation
No 332 45.2
Yes 402 54.8
Deworming
No 334 45.5
Yes 400 54.5
History of Previous Complications
No 283 38.6
Yes 451 61.4
History of Current Illness
No 308 42.0
Yes 426 58.0
History of Frequent Illness
No 331 45.1
Yes 403 54.9
History of Chronic Illness
No 382 52.0
Yes 352 48.0
Substance Use
No 538 73.3
Yes 196 26.7

Household Food Insecurity Access Scale (HFIAS) of the respondents

The findings revealed a high prevalence of household food insecurity among the study participants. The findings showed that only 145 (19.8%) were food secure. More than half, 389 (53.0%), of the households were classified as severely food insecure, while 153 (20.8%) were moderately insecure, and 47 (6.4%) were mildly insecure (Fig 1). More than half of the participants, 474 (64.6%), reported experiencing worry about insufficient food during the four weeks preceding the survey. Similarly, 468 (63.8%) were unable to consume their preferred foods due to limited resources, while 447 (60.9%) indicated reduced dietary variety for the same reason. Furthermore, a considerable proportion of households consumed less preferred or undesirable foods, 450 (61.3%), and experienced reductions in meal size, 462 (62.9%), and frequency of daily meals, 463 (63.1%), because of food scarcity. Alarmingly, 453 (61.7%) of participants reported going to bed hungry, and 462 (62.9%) experienced going a whole day and night without food (Table 3).

Fig 1. Household food insecurity status among pregnant women attending antenatal care in a public hospital in Mogadishu, Somalia (n = 734).

Fig 1

Table 3. Household Food Insecurity Access Scale (HFIAS) among Households Attending Antenatal Care in Public Hospitals in Mogadishu, Somalia (n = 734).

Variables No (%) Yes (%)
Household experienced worry about food being insufficient in the past 4 weeks 260 (35.4) 474 (64.6)
Household members are unable to consume preferred foods due to resource constraints 290 (39.5) 444 (60.5)
Household members are unable to consume the desired foods because of a lack of resources 266 (36.2) 468 (63.8)
Limited dietary variety due to a lack of resources 287 (39.1) 447 (60.9)
Consumption of foods that are less preferred or undesirable due to resource limitations 284 (38.7) 450 (61.3)
Reduction in meal size due to food scarcity 272 (37.1) 462 (62.9)
A decrease in the number of meals per day due to insufficient food 271 (36.9) 463 (63.1)
Going to sleep hungry due to food shortages 281 (38.3) 453 (61.7)

Dietary characteristics and dietary diversity of the participants

Consumption of individual food groups was assessed using binary responses to describe dietary patterns, while overall dietary adequacy was determined using the Dietary Diversity Score (DDS) based on the Minimum Dietary Diversity for Women (MDD-W) indicator. The findings revealed that 416 (56.7%) of the participants had inadequate dietary diversity, while 318 (43.3%) achieved adequate dietary diversity (Fig 2), indicating that the majority did not meet the minimum recommended consumption of at least five food groups. The results showed that a substantial proportion of participants did not consume several nutrient-rich food groups, including grains, white roots, tubers, and plantains (414, 56.4%), nuts and seeds (404, 55.0%), meat, poultry, and fish (410, 55.9%), eggs (441, 60.1%), dark green leafy vegetables (421, 57.4%), vitamin A-rich foods (400, 54.5%), other vegetables (481, 65.5%), and other fruits (444, 60.5%). In contrast, relatively higher proportions reported consuming pulses (412, 56.1%) and dairy products (385, 52.5%) (Table 4)

Fig 2. Dietary Diversity Status of Pregnant Women Attending Antenatal Care in Public Hospitals, Mogadishu, Somalia (n = 734).

Fig 2

Table 4. Consumption of Individual Food Groups Among Pregnant Women Attending Antenatal Care in Public Hospitals in Mogadishu, Somalia (n = 734).

Variables No (%) Yes (%)
Grains, white roots, tubers, and plantains 414 (56.4) 320 (43.6)
Pulses 322 (43.9) 412 (56.1)
Nuts and seeds 404 (55.0) 330 (45.0)
Dairy products 349 (47.5) 385 (52.5)
Meat, poultry, and fish 410 (55.9) 324 (44.1)
Eggs 441 (60.1) 293 (39.9)
Dark green leafy vegetables 421 (57.4) 313 (42.6)
Vitamin A-rich foods 400 (54.5) 334 (45.5)
Other vegetables 481 (65.5) 253 (34.5)
Other fruits 444 (60.5) 290 (39.5)

Nutritional status of participants

In this study, the prevalence of undernutrition (MUAC < 23 cm) among pregnant women attending antenatal care services in public hospitals in Mogadishu was found to be 75.7% (95% CI: 72.6%–78.9%) (Fig 3). The mean MUAC of participants was 21.1 ± 2.6 cm, indicating a generally low average nutritional status within the study population.

Fig 3. Prevalence of undernutrition among pregnant women attending antenatal care in Public Hospitals in Mogadishu, Somalia (n = 734).

Fig 3

Factors associated with undernutrition

Table 5 presents the results of a multivariable logistic regression analysis identifying factors independently associated with undernutrition (MUAC < 23 cm) among pregnant women attending antenatal care in public hospitals in Mogadishu, Somalia. The study identified maternal age, educational level, occupation, household size, residence, income, sanitation access, gestational age, gravidity, contraceptive use, and household food insecurity as significant predictors of maternal undernutrition. The findings are reported as adjusted odds ratios (AOR) with 95% confidence intervals, accounting for potential confounding factors. Statistically significant associations (p < 0.05) are noted.

Table 5. Multivariable analysis of factors associated with undernutrition among pregnant women attending antenatal care in Public Hospitals in Mogadishu, Somalia (n = 734).

Variables Undernutrition(MUAC < 23 cm) COR (95%CI) AOR (95%CI) P Value
Yes No
Age (In Years)
18–24 150 33 1.30 (0.66-2.58) 1.31 (0.61-2.84) 0.491
25–31 180 79 2.60 (1.39-4.86) 2.61 (1.28-5.30) 0.008
32–38 143 52 2.16 (1.13-4.13) 2.18 (1.04-4.55) 0.038
≥ 39 83 14 1
Educational Level
No formal 311 87 1
Primary 139 37 0.95 (0.62-1.47) 1.21 (0.74-2.00) 0.450
Secondary 79 28 1.27 (0.77-2.07) 1.20 (0.73-1.98) 0.467
Tertiary 27 26 3.44 (1.91-6.20) 3.43 (1.89-6.21) <0.001
Occupation
Daily Laborer 76 9 1
Employee 65 50 6.50 (2.97-14.22) 6.38 (2.90-14.04) <0.001
Housewife 380 77 1.71 (0.82-3.56) 1.80 (0.86-3.77) 0.118
Private Business 35 42 10.13 (4.45-23.10) 9.79 (4.27-22.43) <0.001
Family Size
≤ 7 251 47 1 1
> 7 305 131 2.29 (1.58-3.33) 1.96 (1.34-2.88) 0.001
Residence
Rural 126 17 1 1
Urban 430 161 2.78 (1.62-4.75) 2.40 (1.39-4.15) 0.002
HH Monthly Income (In USD)
< 500 333 137 2.24 (1.52-3.30) 1.98 (1.33-2.94) 0.001
≥ 500 223 41 1 1
Presence of U-5 children in the HH
No 225 62 1 1
Yes 331 116 1.27 (0.90-1.81) 1.27 (0.89-1.80) 0.192
Availability of the Latrine facility
No 51 30 2.01 (1.23-3.27) 2.00 (1.23-3.26) 0.005
Yes 505 148 1 1
Age at first marriage
< 18 302 78 1.52 (1.09-2.14) 1.28 (0.88-1.85) 0.201
≥ 18 254 100 1
Trimester of pregnancy
First 508 108 1
Second 37 56 7.12 (4.48-11.33) 8.59 (5.29-13.97) <0.001
Third 11 14 5.99 (2.65-13.55) 6.91 (2.97-16.08) <0.001
Number of Pregnancies
Primigravida 133 59 1.578 (1.09-2.28) 2.29 (1.52-3.45) <0.001
Multigravida 423 119 1
Previous Contraceptive Use
No 220 43 1
Yes 336 135 2.06 (1.40-3.02) 1.98 (1.34-2.90) 0.001
History of Previous Complications
No 201 82 1
Yes 355 96 0.66 (0.47-0.93) 0.74 (0.49-1.11) 0.145
History of Frequent Illness
No 238 93 1
Yes 318 85 0.68 (0.49-0.96) 0.94 (0.62-1.42) 0.761
History of Chronic Illness
No 306 76 1 1
Yes 250 102 1.64 (1.17-2.31) 1.31 (0.92-1.88) 0.139
Substance Use
No 439 99 1
Yes 117 79 2.99 (2.09-4.29) 2.79 (1.93-4.04) <0.001
Household food insecurity status
Food Secure 126 19 1
Mild 38 9 1.57 (0.66-3.76) 1.37 (0.57-3.31) 0.482
Moderate 112 41 2.43 (1.33-4.43) 1.80 (0.97-3.35) 0.063
Severe 280 109 2.58 (1.52-4.39) 1.76 (1.01-3.08) 0.047

Age demonstrated a significant association, with women aged 25–31 years exhibiting 2.61 times higher odds of undernutrition (AOR = 2.61, 95% CI: 1.28–5.30, p = 0.008), and women aged 32–38 years (AOR = 2.18, 95% CI: 1.04–4.55, p = 0.038) were more likely to be undernourished compared to those aged ≥39 years. Educational attainment was significantly associated with undernutrition. Women with a tertiary education had 3.43 times higher odds of undernutrition (AOR = 3.43, 95% CI: 1.89–6.21, p < 0.001) compared to those with no formal education. However, this estimate should be interpreted with caution, as the number of participants in the tertiary education category was relatively small, which may limit the stability and precision of the observed association. This is further reflected in the relatively wide confidence intervals, suggesting potential variability in the estimate. Maternal occupation was significantly associated with nutritional status. Pregnant women employed in private business (AOR = 9.79, 95% CI: 4.27–22.43, p < 0.001) and those employed as workers or employees (AOR = 6.38, 95% CI: 2.90–14.04, p < 0.001) had substantially higher odds of undernutrition compared to daily laborers.

Household size was associated with undernutrition; women from households with more than seven members had significantly higher odds (AOR = 1.96, 95% CI: 1.34–2.88, p = 0.001) compared to those in households with fewer than seven members. Urban residence was significantly associated with increased odds of undernutrition. Women residing in urban areas had significantly higher odds of undernutrition (AOR = 2.40, 95% CI: 1.39–4.15, p = 0.002) compared to those residing in rural areas. Income was a significant determinant, with women from households earning less than USD 500 monthly having approximately twice the odds of undernutrition (AOR = 1.98; 95% CI: 1.33–2.94; p = 0.001) compared to those with higher income levels. Lack of access to latrine facilities also increased the likelihood of undernutrition (AOR = 2.00, 95% CI: 1.23–3.26, p = 0.005).

Gestational age was a significant determinant; women in the second trimester (AOR = 8.59, 95% CI: 5.29–13.97; p < 0.001) and third trimester (AOR = 6.91, 95% CI: 2.97–16.08; p < 0.001) were associated with substantially higher odds of undernutrition compared to those in the first trimester. Primigravid women had significantly higher odds of undernutrition compared to multigravida women (AOR = 2.29, 95% CI: 1.52–3.45, p < 0.001). Women with a history of previous contraceptive use were associated with significantly higher odds of undernutrition compared to those with no history of use (AOR = 1.98, 95% CI: 1.34–2.90, p = 0.001). Substance use was strongly associated with undernutrition, with women reporting substance consumption demonstrating nearly threefold increased odds (AOR = 2.79; 95% CI: 1.93–4.04; p < 0.001) compared to non-users. Household food insecurity was independently associated with undernutrition. Pregnant women from severely food-insecure households had significantly higher odds of undernutrition (AOR = 1.76, 95% CI: 1.01–3.08, p = 0.047) compared to those from food-secure households. Furthermore, some associations with notably large effect sizes, particularly those related to gestational age and occupational categories, should be interpreted with caution, as they may reflect residual confounding, small subgroup sizes, or potential model instability, thereby affecting the robustness of these estimates.

Discussion

The multivariable logistic regression model demonstrated moderate explanatory power, with a Nagelkerke R² value of approximately 0.42. This indicates that approximately 58% of the variability in maternal undernutrition remains unexplained, highlighting the potential influence of unmeasured factors. These may include dietary quantity and caloric intake, micronutrient deficiencies, intra-household food distribution, cultural feeding practices, and displacement status. The absence of these variables may limit the explanatory power of the model and should be considered when interpreting the findings. Although this demonstrates a substantial contribution of the measured factors, a large proportion of the variance remains unexplained. This may be attributable to unmeasured contextual exposures, including protracted conflict, recurrent humanitarian crises, and population displacement. Mogadishu hosts a high concentration of internally displaced persons (IDPs), who are known to experience significantly higher levels of acute malnutrition compared to stable urban residents. The absence of displacement status in the present analysis may partially explain the exceptionally high prevalence of undernutrition observed, representing an important area for future research.

This study found that the prevalence of undernutrition among pregnant women was 75.7%, which is substantially higher than national estimates reported in the Somali Health and Demographic Survey (15%) [20]. This proportion is markedly high, suggesting that maternal undernutrition is a major public health concern in this setting. This discrepancy can be attributed to several important methodological and contextual differences. First, the present study used mid-upper arm circumference (MUAC <23 cm), which is more sensitive to acute undernutrition, whereas national surveys typically rely on body mass index (BMI), which reflects chronic nutritional status. Second, the facility-based design of this study may have captured a higher-risk population, as pregnant women attending ANC services in urban settings are more likely to experience underlying health and nutritional vulnerabilities. Third, Mogadishu is characterized by high levels of urban poverty, population displacement, food insecurity, and reliance on market-based food systems, all of which may contribute to reduced dietary quality and increased risk of undernutrition. These combined factors likely explain the substantially higher prevalence observed in this study. The exceptionally high prevalence observed may also partly reflect the use of a sensitive MUAC cutoff in a predominantly vulnerable urban population attending public referral hospitals.

The prevalence observed in this study is higher than that of studies conducted in the Somali Regional State in Ethiopia (21%) [1], Southwest Ethiopia (42.2%) [29], Kacha Birra District in Southern Ethiopia (52.6%) [30], North Shewa in Ethiopia (22.2%) [31], Tigray in Northern Ethiopia (40.6%) [32], Haramaya District in Eastern Ethiopia (47.9%) [33], Liban District in Ethiopia (44.9%) [34], Chiro District in Eastern Ethiopia (40.9%) [35], Arsi Zone in Ethiopia (48.6%) [36], Konso District in Southern Ethiopia (43.1%) [37], Afar Regional State in Northeast Ethiopia (30.9%) [38], Kenya (27%) [39], Bangladesh (32%) [40], Burundi (34.3%) [41], Tanzania (11%) [42], Zambia (21.8%) [43], Khartoum in Sudan (12.5%) [44], Egypt (31.8%) [45], and systematic review and meta-analysis in the Sub-Saharan Africa region (23.5%) [46], all of which are considerably lower than the findings of our study. This high burden observed in this study could be attributed to several interconnected factors, including prolonged conflict, poverty, recurrent droughts, food insecurity, limited access to quality healthcare and nutritional services, cultural practices influencing diet and health, inadequate awareness about maternal nutrition, and high rates of infectious diseases, all of which may exacerbate nutritional deficiencies and undermine household dietary diversity and access to adequate nutrition.

Age was significantly associated with undernutrition, with women aged 25–38 years being at higher risk compared to those aged 39 years and above. This finding contrasts with studies conducted in Uganda [47]. The increased nutritional risk in these age groups may be attributed to heightened physiological demands and caregiving responsibilities, compounded by socioeconomic constraints. Educational attainment also demonstrated a paradoxical association, whereby women with a tertiary education were more likely to be undernourished than those with no formal education. This finding contrasts with existing evidence in Ethiopia [48], where higher educational status is typically associated with improved nutritional outcomes. However, this result should be interpreted with caution. It may be influenced by residual confounding, small subgroup sizes, or measurement limitations. Additionally, unmeasured socioeconomic factors, such as employment instability or income variability, may partially explain this association. This finding may also reflect the relatively small number of participants with tertiary education in the study population. Further research is needed to better understand this relationship in similar contexts.

Maternal occupation emerged as an important determinant. Pregnant women employed in private business and those employed as employees were significantly more likely to be undernourished compared to daily laborers. Similar findings have been reported in India [49]. The observed occupational differences may reflect variations in socioeconomic conditions, workload patterns, income instability, dietary practices, and access to adequate nutrition among employed women in this setting. However, these findings should be interpreted cautiously because occupational subgroup sizes varied considerably, and residual confounding may persist. Housewives, on the other hand, may have greater opportunities to prioritize rest and food consumption, especially in contexts where men are the primary income earners. Household size was strongly associated with maternal nutritional status. Women living in households with seven or more members were nearly twice as likely to be undernourished compared to those in smaller families. This reflects the principle of “resource dilution,” whereby larger households distribute limited resources across many members, thereby constraining the quantity and quality of food available for pregnant women. Comparable findings have been reported in East Africa [50], where household crowding was associated with poor maternal dietary diversity and undernutrition.

Income levels were significantly associated with nutritional status; women from households earning less than USD 500 monthly had nearly twice the odds of undernutrition compared to those with higher income levels. This finding is corroborated by a study in the Somali Region of Ethiopia [1]where low household income was a determinant of undernutrition among pregnant women. The finding that women living in urban areas had greater odds of undernutrition compared to their rural counterparts contrasts with evidence from a systematic review and meta-analysis in Ethiopia, where rural residence was more commonly associated with maternal malnutrition [4]. This urban disadvantage in Mogadishu could be linked to poverty, overcrowding, displacement, and reliance on purchased food items of poor nutritional quality rather than subsistence farming. Similarly, lack of access to latrine facilities was significantly associated with maternal undernutrition, highlighting the role of sanitation and hygiene in nutritional outcomes. This association aligns with studies in northwest Ethiopia [51], where poor WASH (water, sanitation, and hygiene) practices were linked to increased maternal morbidity and undernutrition.

Gestational age was strongly associated with maternal undernutrition, with women in the second and third trimesters exhibiting significantly higher odds compared to those in the first trimester. Similar associations have been documented in Eastern regions [52], suggesting that as pregnancy advances, maternal nutrient demands increase, and inadequate intake may result in worsening nutritional status. While this finding may reflect increased nutritional demands as pregnancy progresses, it should be interpreted with caution. Physiological changes during pregnancy, including alterations in body composition and fat distribution, may influence mid-upper arm circumference (MUAC) measurements across different gestational stages. As such, MUAC may not remain entirely stable throughout pregnancy, potentially contributing to the observed association. In addition, residual confounding and unmeasured factors may have influenced this relationship. Further investigation is warranted to better understand the dynamics between gestational age and MUAC-based assessment of maternal nutritional status.

Moreover, primigravid women were more likely to be undernourished than multigravida women, corroborating findings from Ethiopia [31], where first-time mothers often lack experience in nutrition and pregnancy care. Previous contraceptive use was positively associated with undernutrition, a finding that may reflect underlying socioeconomic and reproductive health vulnerabilities rather than a direct biological effect. Women with a history of contraceptive use may represent those with closely spaced pregnancies, prior nutritional depletion, or limited access to comprehensive reproductive health and nutrition services. Similar associations have been reported in other low-resource settings, where contraceptive use serves as a proxy for broader reproductive health challenges rather than a protective factor in isolation. Substance use was also strongly associated with undernutrition, consistent with reports from Ethiopia [53], where khat chewing and alcohol consumption were linked to poor maternal nutritional outcomes. Furthermore, household food insecurity was significantly associated with maternal undernutrition. Women from severely food-insecure households had higher odds of undernutrition compared to those from food-secure households. This finding is consistent with evidence from a study in the Somali region of Ethiopia [1], indicating that food insecurity is an important contributing factor to maternal undernutrition, as it directly limits access to adequate and nutritious food and contributes to poor dietary quality. Furthermore, the high prevalence of severe household food insecurity observed in this study suggests a potential interaction with other socioeconomic and demographic factors, including income level, household size, and maternal occupation, in shaping maternal nutritional outcomes. However, these interactions were not formally examined in the present analysis and should be explored in future research to better understand their combined effects.

Strengths and limitations

This study is among the first to document the prevalence and determinants of maternal undernutrition in Mogadishu, using a large sample size, a high response rate, and standardized tools such as MUAC and HFIAS, which strengthen the validity of the findings. The use of multivariable analysis also allowed for robust identification of independent predictors. However, this study has several limitations that should be considered when interpreting the findings. First, the cross-sectional design limits causal inference, and reliance on self-reported data may have introduced recall bias. Second, the facility-based design may have introduced selection bias, as only pregnant women attending antenatal care services were included, thereby excluding those who do not access health facilities and potentially limiting the generalizability of the results. Third, dietary intake was assessed using a 24-hour recall method, which is subject to recall bias and may not accurately reflect habitual dietary patterns. Additionally, although multiple variables were included in the analysis, residual confounding may persist due to unmeasured factors such as displacement status, cultural dietary practices, and intra-household food allocation. The disproportionately high proportion of first-trimester participants may reflect antenatal care attendance patterns, referral dynamics, or sampling variation during the study period and may have limited the representativeness of gestational age-related findings. These limitations should be taken into account when interpreting the study findings.

Conclusion

This study demonstrated a high prevalence of maternal undernutrition among pregnant women attending antenatal care services in public hospitals in Mogadishu. Maternal age, educational level, occupation, household size, residence, income, sanitation access, gestational age, gravidity, contraceptive use, substance use, and household food insecurity were identified as being associated with maternal undernutrition. These findings highlight the need for targeted, multi-sectoral interventions aimed at improving maternal nutritional status, including strengthening food security, enhancing nutrition education, and improving access to quality maternal healthcare services. However, these recommendations are informed by observed associations and should be interpreted with caution, as causal relationships cannot be established from this study. Integrating maternal nutrition screening and targeted nutritional support into routine antenatal care services is essential in fragile and humanitarian settings such as Somalia.

Acknowledgments

The authors would like to extend their gratitude to the study participants for their cooperation and willingness to take part in the research. We also thank the staff of Benadir, Demartino, and SOS Hospitals for their support during data collection. Special appreciation is given to the Research and Innovation Center of Zamzam University of Science and Technology for granting the necessary permissions to conduct this study.

Abbreviations

AOR

adjusted odds ratio

ANC

antenatal care

BMI

body mass index

CI

confidence interval

COR

crude odds ratio

FMOH

Federal Ministry of Health

HFIAS

household food insecurity access scale

IRB

institutional review board

IUGR

intrauterine growth restriction

LMICs

low- and middle-income countries

MUAC

mid-upper arm circumference

RIC

research and innovation center

SDGs

sustainable development goals

SPSS

statistical package for the social sciences

UNICEF

United Nations Children’s Fund

USD

United States Dollar

WASH

water, sanitation, and hygiene

WHO

World Health Organization

ZUST

Zamzam University of Science and Technology

Data Availability

The datasets generated and/or analyzed during the current study are not publicly available because they contain potentially identifiable participant information and are subject to ethical and confidentiality restrictions imposed by the Institutional Review Board (IRB) of Zamzam University of Science and Technology. Researchers who meet the criteria for access to confidential data may request access through the Institutional Review Board (IRB), Zamzam University of Science and Technology, Mogadishu, Somalia. Data access requests can be directed to the IRB Secretariat at ric@zust.edu.so. The IRB will review requests and determine whether access can be granted in accordance with ethical approval requirements and participant confidentiality protections.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Jianhong Zhou

8 Jan 2026

-->PONE-D-25-46984-->-->Prevalence of Undernutrition and Its Associated Factors Among Pregnant Women Attending Antenatal Care Service in Public Hospitals in Mogadishu, Somalia-->-->PLOS One

Dear Dr. Tahlil,

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Reviewer #1: Partly

**********

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Reviewer #1: Yes

**********

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Reviewer #1: Yes

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Reviewer #1: Preamble: This study assessed the prevalence and associated factors of undernutrition among

pregnant women attending antenatal care (ANC) services in public hospitals in Mogadishu. The findings may inform public health interventions and help in designing strategies to enhance maternal nutrition.

Main Concerns

The following are some concerns that need to be addressed to make the paper publishable.

INTRODUCTION

• There is a general problem of referencing sentences because the citations are placed after “a full stop”. For example, “Undernutrition among pregnant women remains a significant public health challenge worldwide, particularly in low- and middle-income countries such as Somalia, where socioeconomic disparities, limited healthcare access, and food insecurity are prevalent. [1]”

• To address the problem of citation placement, the authors should follow standard academic formatting rules based on the specific style guide:

Standard Placement (Before the Period)

i. In most citation styles, including AMA, APA, and MLA, the reference is considered part of the sentence and must be placed before the final punctuation.

ii. Example (APA/MLA): ...particularly in low- and middle-income countries such as Somalia (Smith, 2025).

iii. Example (Vancouver/AMA): ...limited healthcare access and food insecurity are prevalent [1].

• The justification for the study appears unclear because the authors have stated on pages 2-3 that “According to the Somali Health and Demographic Survey 2020, approximately 15% of pregnant women in Somalia experience undernutrition. [20]”. However, the authors went ahead to indicate that “Despite these challenges, evidence on the prevalence and determinants of undernutrition among pregnant women in Mogadishu remains limited. Existing studies in Somalia have primarily focused on anemia or child malnutrition. This study aims to assess the prevalence of undernutrition and its associated factors among pregnant women attending ANC services in public hospitals in Mogadishu, Somalia’ What form of undernutrition are the authors seeking to investigate in the present study? The authors should clearly explain what is so unique about the study and how their assessment of undernutrition of pregnant women is different from what is reported in the Somali Health and Demographic Survey 2020 and other similar studies carried out in the country.

METHODS

Assessment of dietary intake, and food security

i. Household Food Insecurity Access Scale (HFIAS): the authors should provide details of how this was actually measured. What were the parameters used?

ii. Explain how dietary intake patterns of pregnant women were classified as either adequate or inadequate.

Statistical analysis

Before applying binary logistic regression, how was the presence of multi-collinearity among the independent variable diagnosed?

RESULTS

• The finding that attainment of tertiary education was a risk factor for undernutrition (AOR= 3.43, 95% CI: 1.89–6.21) is unusual, as higher education is typically associated with better nutritional outcomes due to increased knowledge and income potential. Ultimately, the finding is likely a result of local socioeconomic realities and contextual factors that override the typical benefits of education, rather than an inherent risk of education itself.

• This counter-intuitive result is likely explained by specific contextual factors of the study area, which may include:

a. Socioeconomic Disparities: Women with higher education might still face significant economic constraints, such as high unemployment or low income, if the local job market is poor. Undernutrition is often strongly linked to low household income and food insecurity, regardless of education level.

b. Competing Demands and Lifestyle: Pursuing tertiary education or related careers can involve time constraints and high stress, potentially leading to poor dietary practices, meal skipping, or reliance on less nutritious convenience foods.

DISCUSSION OF STUDY RESULTS

i. As quantified by the Nagelkerke R Square in the logistic regression analyses, what percentage of the variance of maternal undernutrition is accounted for by the measured risk factors? The 75 % of undernutrition in Mogadishu is really alarming and this may be attributed to an unmeasured exposure including the ongoing humanitarian crisis and displacement. Mogadishu being the national capital city could be hosting millions displaced persons (IDP Concentrations). These populations often show much higher rates of acute malnutrition than stable urban residents. It would therefore be interesting to see how undernutrition varies with whether respondents were normal residents or displaced.

ii. What possibly explains why attainment of tertiary education was risk factor for undernutrition among pregnant women. This counter-intuitive result is likely explained by specific contextual factors of the study area, which may include:

a. Socioeconomic Disparities: Women with higher education might still face significant economic constraints, such as high unemployment or low income, if the local job market is poor. Undernutrition is often strongly linked to low household income and food insecurity, regardless of education level.

b. Competing Demands and Lifestyle: Pursuing tertiary education or related careers can involve time constraints and high stress, potentially leading to poor dietary practices, meal skipping, or reliance on less nutritious convenience foods.

iii. Similarly, previous contraceptive use associated positively with undernutrition. What accounts for this? And are there similar results in the literature?

**********

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Reviewer #1: Yes:  Dr. Mahama Saaka

**********

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PLoS One. 2026 Jul 7;21(7):e0347187. doi: 10.1371/journal.pone.0347187.r002

Author response to Decision Letter 1


28 Jan 2026

POINT-BY-POINT REVIEWER'S RESPONSE

Reviewer’s Comment Author’s Response

Preamble: This study assessed the prevalence and associated factors of undernutrition among pregnant women attending antenatal care (ANC) services in public hospitals in Mogadishu. The findings may inform public health interventions and help in designing strategies to enhance maternal nutrition. We thank the reviewer for this positive overview of the study and for recognizing its potential contribution to informing public health interventions and maternal nutrition strategies in Mogadishu, Somalia.

INTRODUCTION: There is a general problem of referencing sentences because the citations are placed after “a full stop”. For example, “Undernutrition among pregnant women remains a significant public health challenge worldwide, particularly in low- and middle-income countries such as Somalia, where socioeconomic disparities, limited healthcare access, and food insecurity are prevalent. [1]” We appreciate the reviewer’s observation. The manuscript has been carefully revised to ensure that all citations are placed according to standard academic referencing conventions. Specifically, references are now positioned before the final punctuation in accordance with Vancouver citation style (e.g., “…food insecurity are prevalent [1].”). This correction has been applied consistently throughout the entire manuscript, particularly in the Introduction section.

To address the problem of citation placement, the authors should follow standard academic formatting rules based on the specific style guide. The authors have fully adhered to this recommendation. All in-text citations have been reformatted to comply with the journal’s referencing style, ensuring consistency and adherence to accepted academic standards.

The justification for the study appears unclear… What form of undernutrition are the authors seeking to investigate in the present study? The authors should clearly explain what is so unique about the study and how their assessment of undernutrition of pregnant women is different from what is reported in the Somali Health and Demographic Survey 2020 and other similar studies carried out in the country. We thank the reviewer for highlighting this important point. The Introduction has been substantially revised to clearly clarify the study’s justification and uniqueness. We now explicitly state that while the Somali Health and Demographic Survey (SHDS) 2020 reports national estimates of maternal undernutrition primarily based on BMI, the present study focuses on acute maternal undernutrition assessed using mid-upper arm circumference (MUAC < 23 cm). MUAC is a sensitive indicator recommended for identifying current nutritional risk among pregnant women, particularly in emergency and resource-limited settings such as Mogadishu. Furthermore, this study is facility-based, urban-specific, and incorporates contextual determinants such as household food insecurity, occupation, and sanitation, which are not adequately captured in national surveys.

METHODS – Assessment of dietary intake and food security: Household Food Insecurity Access Scale (HFIAS): the authors should provide details of how this was actually measured. What were the parameters used? The Methods section has been revised to include a detailed description of the HFIAS. We now specify that the scale consists of nine occurrence questions assessing anxiety about food supply, food quality, and food quantity over the previous four weeks, followed by frequency-of-occurrence questions. Households were categorized into food secure, mildly, moderately, and severely food insecure according to standard HFIAS guidelines.

Explain how dietary intake patterns of pregnant women were classified as either adequate or inadequate. We have clarified this in the Methods section. Dietary intake was assessed using a 24-hour dietary recall, and consumption was categorized as “adequate” if at least one food item from a given food group was consumed during the recall period and “inadequate” if none was consumed. This approach is consistent with commonly used dietary diversity assessment methods in similar settings.

Statistical analysis: Before applying binary logistic regression, how was the presence of multicollinearity among the independent variables diagnosed? We appreciate this comment. The Data Analysis subsection has been updated to indicate that multicollinearity was assessed using Variance Inflation Factors (VIF). A VIF value greater than 10 was considered indicative of multicollinearity, and no such values were observed, confirming the suitability of the regression model.

RESULTS: The finding that attainment of tertiary education was a risk factor for undernutrition is unusual… We acknowledge the reviewer’s concern. The Results section now includes a brief clarifying statement noting that this finding likely reflects contextual socioeconomic realities rather than an inherent risk of education itself. No changes were made to the statistical results, but interpretation has been carefully contextualized.

DISCUSSION: As quantified by the Nagelkerke R Square in the logistic regression analyses, what percentage of the variance of maternal undernutrition is accounted for by the measured risk factors? Thank you for this important observation. The Discussion section has been revised to report the Nagelkerke R² value, indicating the proportion of variance in maternal undernutrition explained by the model. We further acknowledge that a substantial proportion of the variance remains unexplained, suggesting the influence of unmeasured factors.

The 75% of undernutrition in Mogadishu is really alarming and this may be attributed to an unmeasured exposure including the ongoing humanitarian crisis and displacement… We fully agree with the reviewer. The Discussion has been expanded to highlight the role of prolonged humanitarian crises, urban poverty, and the high concentration of internally displaced persons (IDPs) in Mogadishu as plausible contributors to the extremely high prevalence of maternal undernutrition observed in this study. We also acknowledge displacement status as an important unmeasured variable and recommend its inclusion in future research.

What possibly explains why attainment of tertiary education was a risk factor for undernutrition among pregnant women? The Discussion has been strengthened to provide a detailed contextual explanation. We now discuss how tertiary education in Somalia does not necessarily translate into stable employment or improved income for women, particularly in Mogadishu, where unemployment, informal labor, and occupational stress may override the expected nutritional benefits of education.

Similarly, previous contraceptive use associated positively with undernutrition. What accounts for this? And are there similar results in the literature? We thank the reviewer for this insightful comment. A new paragraph has been added to the Discussion explaining that previous contraceptive use may reflect cumulative reproductive stress, short birth intervals, or underlying socioeconomic vulnerability rather than a direct causal effect. We also note that similar associations have been reported in other low-resource settings and cite supporting literature accordingly.

Attachment

Submitted filename: Point-by-point Reviewers Response.docx

pone.0347187.s001.docx (16.8KB, docx)

Decision Letter 1

Helen Howard

27 Apr 2026

<div>PONE-D-25-46984R1-->-->Prevalence of Undernutrition and Its Associated Factors Among Pregnant Women Attending Antenatal Care Service in Public Hospitals in Mogadishu, Somalia-->-->PLOS One

Dear Dr. Tahlil,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jun 08 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Yes

Reviewer #2: Partly

**********

-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: Yes

Reviewer #2: No

**********

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: No

**********

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Reviewer #2: Yes

**********

-->6. Review Comments to the Author

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Reviewer #1: Main Concerns

Although most of my earlier concerns have been addressed, there are still a few that should be attended to make the paper publishable.

METHODS

Assessment of dietary diversity, and food security

i. Household Food Insecurity Access Scale (HFIAS): the authors should provide the reference that gives details of how this was actually measured?

ii. The explanation given for classifying dietary intake patterns of pregnant women as either adequate or inadequate is still not clear. According to the authors, food items consumed were grouped according to standard food groups (what does “standard” refer to here? how many food groups were involved). The authors also categorized. dietary intake as “adequate” if at least one food item from a given food group was consumed during the recall period and “inadequate” if none was consumed. So, if a woman was classified as adequate for a particular food group but inadequate for another food group, how then did the authors describe the dietary intake patterns of this woman? Let me just mention that there is a difference between food variety and dietary diversity. Dietary diversity and food variety are distinct nutritional concepts, often used to measure diet quality, with dietary diversity counting different food groups consumed while food variety counts the total number of individual food items.

Food Variety Score (FVS): This is a simple count of the individual food items consumed over a specific period (e.g., 24 hours). For instance, eating an apple, a banana, and a pear would count as a variety of three items.

Dietary Diversity Score (DDS): This measures the number of food groups represented in a diet. Using the same example, an apple, a banana, and a pear would only count as one for dietary diversity because they all belong to the "fruit" group.

STUDY RESULTS

The results presented in Table 4 could be improved to show the overall dietary diversity of pregnant women. Dietary adequacy should not be based only on individual food groups but all the food groups. For example, the minimum dietary diversity for women (MDD-W) is achieved if the woman consumes five or more of the 10 defined food groups. Studies indicate that dietary diversity is often a more effective predictor of overall nutrient adequacy because consuming foods from multiple groups provides a better balance of energy, protein, and minerals than simply eating many different items within a single group.

Reviewer #2: Abstract

1. The reported prevalence of undernutrition (75.7%) is exceptionally high and requires contextual qualification. Please briefly acknowledge in the Abstract that this estimate is based on MUAC (<23 cm) and a facility-based sample, which may limit comparability with national estimates.

2. (Results section): Several adjusted odds ratios (e.g., private business AOR = 9.79; second trimester AOR = 8.59) appear unusually large. Consider adding a short cautionary phrase indicating that these associations should be interpreted carefully.

Introduction

3. While the background is comprehensive, the distinction between BMI-based national estimates and MUAC-based assessment should be more clearly and concisely articulated earlier in the section to strengthen the study rationale.

4. The justification for focusing on an urban, facility-based population is improved but could be further sharpened by explicitly stating why ANC attendees in Mogadishu represent a high-risk subgroup.

Methods (Study Design): The facility-based cross-sectional design should be more explicitly acknowledged as limiting generalizability, particularly given that women not attending ANC are excluded.

5. (Sampling): Additional clarity is needed regarding how the sampling interval (k) was operationalized in each hospital. Providing a brief example would improve reproducibility.

6. (Anthropometry): The use of MUAC <23 cm as a cutoff requires stronger justification with citation of WHO or emergency nutrition guidelines, as this threshold critically influences the prevalence estimate.

7. (Dietary Assessment): The classification of dietary intake as “adequate” based on consumption of at least one item per food group over 24 hours appears overly simplistic. This should be reframed as “food group consumption” rather than adequacy.

8. (Statistical Analysis): While VIF was used to assess multicollinearity, additional details on model-building strategy (e.g., theoretical vs stepwise selection) would strengthen transparency. The choice of p<0.25 for inclusion in multivariable analysis should be justified with a citation or brief rationale.

Results

9. (Prevalence): The very high prevalence (75.7%) requires further descriptive support. Reporting the mean and distribution (e.g., SD or percentiles) of MUAC would help readers assess plausibility.

10. (Table 5): Some categories (e.g., tertiary education, n=53) are relatively small, yet show strong associations (AOR = 3.43). Please comment on the stability of these estimates.

11. (Regression findings): The magnitude of certain associations (e.g., second trimester AOR = 8.59; private business AOR = 9.79) raises concern for residual confounding or model instability. This should be acknowledged.

12. Interpretive language is occasionally used (e.g., explanation of education findings). Interpretation should be reserved for the Discussion section.

Discussion

13. (Prevalence): While comparisons with other countries are extensive, the discussion should more critically address why the prevalence in this study is substantially higher than both national (15%) and regional estimates.

14. (Education finding): The explanation provided for tertiary education being associated with undernutrition is speculative. It would be helpful to explicitly acknowledge alternative explanations such as confounding or measurement bias.

15. (Trimester effect): The very strong association between trimester and undernutrition requires cautious interpretation. Consider discussing whether MUAC changes across pregnancy stages may influence this finding.

16. (Model performance): The reported Nagelkerke R² (~42%) is mentioned but not critically interpreted. Please clarify what proportion of variability remains unexplained and what key variables may be missing.

17. (Bias): Selection bias (facility-based sample), recall bias (24-hour dietary recall), and unmeasured confounders (e.g., displacement status) should be more explicitly discussed.

18. (Food insecurity): Given that over half of households were severely food insecure, the interaction between food insecurity and other predictors could be explored or at least acknowledged.

Conclusion

19. The conclusions are currently somewhat strong relative to the observational design. Statements implying causality should be softened (e.g., replace “determinants” with “associated factors”).

20. Policy recommendations are appropriate but should be framed as being based on associative evidence rather than causal inference.

21. Data Availability: The statement that data are “available upon reasonable request” does not meet PLOS ONE requirements. Please revise to include a public repository or provide a justified exception.

22. Overall clarity: The manuscript is generally well-structured, but minor language refinement would improve readability, particularly in the Results and Discussion sections.

**********

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Reviewer #1: Yes:  Mahama Saaka

Reviewer #2: Yes:  Abu Ansar Md Rizwan

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PLoS One. 2026 Jul 7;21(7):e0347187. doi: 10.1371/journal.pone.0347187.r004

Author response to Decision Letter 2


29 Apr 2026

POINT-BY-POINT REVIEWER'S RESPONSE

Reviewer 1

Reviewer’s Comment Author’s Response

METHODS – Assessment of dietary diversity, and food security

i. Household Food Insecurity Access Scale (HFIAS): the authors should provide the reference that gives details of how this was actually measured? Thank you for this important comment. We have revised the Methods section to clearly describe the HFIAS measurement and included the appropriate reference (FANTA guideline). Specifically, we now state that HFIAS consists of nine standardized occurrence questions covering three domains (anxiety, food quality, and food intake), with frequency-of-occurrence responses used to classify households into four categories (food secure, mildly, moderately, and severely food insecure).

ii. The explanation given for classifying dietary intake patterns of pregnant women as either adequate or inadequate is still not clear. According to the authors, food items consumed were grouped according to standard food groups (what does “standard” refer to here? how many food groups were involved). We appreciate this clarification request. The Methods section has been revised to explicitly define “standard food groups” as the ten food groups specified by the Minimum Dietary Diversity for Women (MDD-W) indicator. These ten groups are now clearly listed in the manuscript to ensure transparency and reproducibility.

The authors also categorized dietary intake as “adequate” if at least one food item from a given food group was consumed during the recall period and “inadequate” if none was consumed. Thank you for highlighting this ambiguity. We have revised the manuscript to clarify that consumption of individual food groups was used only to describe dietary patterns, not to determine overall dietary adequacy.

So, if a woman was classified as adequate for a particular food group but inadequate for another food group, how then did the authors describe the dietary intake patterns of this woman? We have addressed this concern by clearly distinguishing between food group consumption and overall dietary adequacy. Specifically, we now state that overall dietary adequacy was determined using the Dietary Diversity Score (DDS), which summarizes the number of food groups consumed. Individual food group consumption is presented descriptively and does not determine overall adequacy.

Let me just mention that there is a difference between food variety and dietary diversity. We thank the reviewer for this important distinction. The Methods section has been revised to explicitly differentiate between food variety (number of individual food items consumed) and dietary diversity (number of food groups consumed). This clarification aligns with established nutritional assessment frameworks.

Food Variety Score (FVS): This is a simple count of the individual food items consumed over a specific period… We acknowledge this explanation and have incorporated the conceptual distinction into the manuscript. We clarify that our study used Dietary Diversity Score (DDS), not Food Variety Score (FVS), to assess overall diet quality.

Dietary Diversity Score (DDS): This measures the number of food groups represented in a diet… We have revised the Methods section to clearly describe DDS calculation based on the ten MDD-W food groups. We also specified the cut-off point, where consumption of ≥5 food groups indicate adequate dietary diversity, consistent with international guidelines.

STUDY RESULTS

The results presented in Table 4 could be improved to show the overall dietary diversity of pregnant women. Thank you for this suggestion. We have revised the Results section to prioritize Dietary Diversity Score (DDS) as the main indicator of overall dietary adequacy. The DDS findings are now presented first before describing individual food group consumption.

Dietary adequacy should not be based only on individual food groups but all the food groups. We agree and have addressed this by clarifying that overall dietary adequacy is determined using DDS (based on all food groups combined), rather than individual food groups. Individual food group consumption is now clearly presented as descriptive information only.

For example, the minimum dietary diversity for women (MDD-W) is achieved if the woman consumes five or more of the 10 defined food groups. This recommendation has been incorporated into the manuscript. We now explicitly state that adequate dietary diversity is defined as consumption of at least five out of the ten MDD-W food groups.

Studies indicate that dietary diversity is often a more effective predictor of overall nutrient adequacy… We appreciate this insight and have strengthened the manuscript by emphasizing that DDS is a proxy indicator of micronutrient adequacy and overall diet quality, consistent with established literature. Additionally, the Results section has been revised to reflect this emphasis.

Reviewer 2

Reviewer’s Comment Author’s Response

1. The reported prevalence of undernutrition (75.7%) is exceptionally high and requires contextual qualification. Please briefly acknowledge in the Abstract that this estimate is based on MUAC (<23 cm) and a facility-based sample, which may limit comparability with national estimates. We thank the reviewer for this important observation. The Abstract has been revised to clearly indicate that the reported prevalence is based on MUAC (<23 cm) and a facility-based sample, which may limit comparability with national estimates derived from BMI-based population surveys.

2. (Results section): Several adjusted odds ratios (e.g., private business AOR = 9.79; second trimester AOR = 8.59) appear unusually large. Consider adding a short cautionary phrase indicating that these associations should be interpreted carefully. We appreciate this comment. A cautionary statement has been added to the Results section indicating that large effect sizes should be interpreted with caution due to potential residual confounding, small subgroup sizes, or model instability.

3. While the background is comprehensive, the distinction between BMI-based national estimates and MUAC-based assessment should be more clearly and concisely articulated earlier in the section to strengthen the study rationale. We thank the reviewer for this suggestion. The Introduction has been revised to more clearly and concisely distinguish between BMI-based national estimates and MUAC-based assessment earlier in the section.

4. The justification for focusing on an urban, facility-based population is improved but could be further sharpened by explicitly stating why ANC attendees in Mogadishu represent a high-risk subgroup. We appreciate this comment. The Introduction has been strengthened by explicitly stating that ANC attendees in Mogadishu represent a high-risk subgroup due to urban poverty, displacement, and food insecurity.

Methods (Study Design): The facility-based cross-sectional design should be more explicitly acknowledged as limiting generalizability, particularly given that women not attending ANC are excluded. We thank the reviewer for this important point. The limitation of the facility-based cross-sectional design in restricting generalizability has been explicitly acknowledged in the Discussion section.

5. (Sampling): Additional clarity is needed regarding how the sampling interval (k) was operationalized in each hospital. Providing a brief example would improve reproducibility. We appreciate this suggestion. A detailed example illustrating how the sampling interval (k) was calculated and applied has been added to improve clarity and reproducibility.

6. (Anthropometry): The use of MUAC <23 cm as a cutoff requires stronger justification with citation of WHO or emergency nutrition guidelines, as this threshold critically influences the prevalence estimate. We thank the reviewer. The manuscript has been revised to include stronger justification for the MUAC <23 cm cutoff, supported by WHO and emergency nutrition guidelines.

7. (Dietary Assessment): The classification of dietary intake as “adequate” based on consumption of at least one item per food group over 24 hours appears overly simplistic. This should be reframed as “food group consumption” rather than adequacy. We appreciate this important comment. The terminology has been revised throughout the manuscript to reflect “food group consumption (Yes/No)” rather than adequacy, and overall dietary adequacy is now determined using DDS.

8. (Statistical Analysis): While VIF was used to assess multicollinearity, additional details on model-building strategy (e.g., theoretical vs stepwise selection) would strengthen transparency. The choice of p<0.25 for inclusion in multivariable analysis should be justified with a citation or brief rationale. We thank the reviewer. The model-building strategy has been clarified to include both statistical and theoretical considerations, and justification for the use of p<0.25 has been provided.

9. (Prevalence): The very high prevalence (75.7%) requires further descriptive support. Reporting the mean and distribution (e.g., SD or percentiles) of MUAC would help readers assess plausibility. We appreciate this comment. The mean and standard deviation of MUAC have been included to provide additional descriptive support for the reported prevalence.

10. (Table 5): Some categories (e.g., tertiary education, n=53) are relatively small, yet show strong associations (AOR = 3.43). Please comment on the stability of these estimates. We thank the reviewer. A statement has been added acknowledging that small subgroup sizes may affect the stability and precision of the estimates.

11. (Regression findings): The magnitude of certain associations (e.g., second trimester AOR = 8.59; private business AOR = 9.79) raises concern for residual confounding or model instability. This should be acknowledged. We appreciate this comment. A statement has been added acknowledging that large effect sizes may reflect residual confounding or model instability.

12. Interpretive language is occasionally used (e.g., explanation of education findings). Interpretation should be reserved for the Discussion section. We thank the reviewer. Interpretive language has been removed from the Results section and appropriately relocated to the Discussion section.

13. (Prevalence): While comparisons with other countries are extensive, the discussion should more critically address why the prevalence in this study is substantially higher than both national (15%) and regional estimates. We appreciate this comment. The Discussion has been strengthened to critically explain the higher prevalence based on methodological and contextual differences.

14. (Education finding): The explanation provided for tertiary education being associated with undernutrition is speculative. It would be helpful to explicitly acknowledge alternative explanations such as confounding or measurement bias. We thank the reviewer. The explanation has been revised to reduce speculation and to acknowledge potential confounding and measurement bias.

15. (Trimester effect): The very strong association between trimester and undernutrition requires cautious interpretation. Consider discussing whether MUAC changes across pregnancy stages may influence this finding. We appreciate this suggestion. The Discussion now includes a cautious interpretation and consideration of physiological changes affecting MUAC during pregnancy.

16. (Model performance): The reported Nagelkerke R² (~42%) is mentioned but not critically interpreted. Please clarify what proportion of variability remains unexplained and what key variables may be missing. We thank the reviewer. The Discussion has been expanded to interpret the unexplained variance and identify potential missing variables.

17. (Bias): Selection bias (facility-based sample), recall bias (24-hour dietary recall), and unmeasured confounders (e.g., displacement status) should be more explicitly discussed. We appreciate this comment. The limitations section has been strengthened to explicitly address these biases.

18. (Food insecurity): Given that over half of households were severely food insecure, the interaction between food insecurity and other predictors could be explored or at least acknowledged. We thank the reviewer. A statement has been added acknowledging potential interactions and recommending further research.

19. The conclusions are currently somewhat strong relative to the observational design. Statements implying causality should be softened (e.g., replace “determinants” with “associated factors”). We appreciate this comment. The Conclusion has been revised to remove causal language and replace it with associative terminology.

20. Policy recommendations are appropriate but should be framed as being based on associative evidence rather than causal inference. We thank the reviewer. Policy recommendations have been reframed to reflect that they are based on observed associations.

21. Data Availability: The statement that data are “available upon reasonable request” does not meet PLOS ONE requirements. Please revise to include a public repository or provide a justified exception. We appreciate this comment. The data availability statement has been revised to reflect ethical restrictions and IRB approval requirements.

22. Overall clarity: The manuscript is generally well-structured, but minor language refinement would improve readability, particularly in the Results and Discussion sections. We thank the reviewer for this helpful suggestion. The manuscript has been carefully revised to improve clarity, coherence, and readability, particularly in the Results and Discussion sections.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0347187.s002.docx (20.1KB, docx)

Decision Letter 2

Olutosin Ademola Otekunrin

25 May 2026

-->PONE-D-25-46984R2-->-->Prevalence of Undernutrition and Its Associated Factors Among Pregnant Women Attending Antenatal Care Service in Public Hospitals in Mogadishu, Somalia-->-->PLOS One

Dear Dr. Tahlil,

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Reviewer #1: All comments have been addressed

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes: Dr, Mahama Saaka

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PLoS One. 2026 Jul 7;21(7):e0347187. doi: 10.1371/journal.pone.0347187.r006

Author response to Decision Letter 3


10 Jun 2026

POINT-BY-POINT REVIEWER'S RESPONSE

Reviewer/Editor Comment Author Response

Thank you for providing the Data Availability Statement. We note that your underlying data are restricted for ethical or legal reasons. PLOS journals' data policy does not allow authors to be the sole contact for access to restricted data. Please provide contact information for a non-author institutional point of contact who can field data inquiries from fellow researchers and update the Data Availability Statement accordingly. Thank you for this important observation. We have revised the Data Availability Statement to comply with PLOS ONE's data-sharing requirements. Specifically, we have replaced the corresponding author as the sole contact for data access and included a non-author institutional point of contact through the Institutional Review Board (IRB) of Zamzam University of Science and Technology. Researchers seeking access to the restricted dataset may now submit requests directly to the IRB, which will review requests and determine eligibility for data access in accordance with ethical approval requirements and participant confidentiality protections.

Decision Letter 3

Olutosin Ademola Otekunrin

18 Jun 2026

Prevalence of Undernutrition and Its Associated Factors Among Pregnant Women Attending Antenatal Care Service in Public Hospitals in Mogadishu, Somalia

PONE-D-25-46984R3

Dear Dr. Tahlil,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Olutosin Ademola Otekunrin, PhD

Academic Editor

PLOS One

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Reviewer #1: Yes

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Reviewer #1: Yes

**********

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Reviewer #1: Yes:  Mahama Saaka

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Acceptance letter

Olutosin Ademola Otekunrin

PONE-D-25-46984R3

PLOS One

Dear Dr. Tahlil,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team.

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Academic Editor

PLOS One

Associated Data

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

    Supplementary Materials

    Attachment

    Submitted filename: Point-by-point Reviewers Response.docx

    pone.0347187.s001.docx (16.8KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    pone.0347187.s002.docx (20.1KB, docx)

    Data Availability Statement

    The datasets generated and/or analyzed during the current study are not publicly available because they contain potentially identifiable participant information and are subject to ethical and confidentiality restrictions imposed by the Institutional Review Board (IRB) of Zamzam University of Science and Technology. Researchers who meet the criteria for access to confidential data may request access through the Institutional Review Board (IRB), Zamzam University of Science and Technology, Mogadishu, Somalia. Data access requests can be directed to the IRB Secretariat at ric@zust.edu.so. The IRB will review requests and determine whether access can be granted in accordance with ethical approval requirements and participant confidentiality protections.


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