An unmatched case–control study was conducted in five SAM-affected kebeles (such as Korile, Dembel, Gumtameli, Sekoyta, and Galimeda), which are small administrative units in Dubti District of Afar, Northeastern Ethiopia, from 1 May 2022 to 30 May 2022. This area is located 600 km from Addis Ababa, the capital city of Ethiopia. The district has 13 kebeles and 10,992 households. Based on 2007 census data, the total population of the district for 2022–2023 was estimated to be 49,173. The district is one of the hotspot areas for under-five malnutrition in the region, characterized by recurrent droughts and pastoral communities that rely on livestock production. The prevalence rates of wasting, stunting, and underweight were estimated to be 16.2, 43.1, and 24.8%, respectively (19).

All under-five children living in the five malnutrition-affected kebeles in Dubti District comprised the study population. Cases were defined as children aged 6–59 months with a weight-for-height score (WFH) of less than −3 standard deviations (SDs), a mid-upper arm circumference (MUAC) of less than 110 mm, or bilateral pitting edema (20). Controls were defined as children of the same age with WFH score greater than −2 SDs and/or MUAC greater than 125 mm (21). Children with congenital anomalies, including Down syndrome, and physical deformities that interfered with the standard anthropometric procedure, as well as those whose mothers or caregivers failed to provide informed consent, were excluded from the study.

We used all SAM cases identified in the line list for descriptive analysis. For the analytic study, the sample size was calculated using Epi-Info software version 7.1.1.0 based on the following assumptions: power (80%), 95% confidence interval (CI), a case-to-control ratio of 1:2, and findings from a previous study that identified prelacteal feedings as risk factors for SAM (19). Therefore, by considering the percentage of controls exposed (78.6%), the percentage of cases exposed (93.3%), an odds ratio of 3.81, and a 10% non-response rate, the final calculated sample size was 258, comprising 86 cases and 172 controls.

Mathematically, N = r + 1 p − q − Z β + Z α / 2 2 r p 1 − p 2 + 10 % non-response rate.

where N = sample size, P1 = percentage of cases exposed (93.3%), P2 = percentage of controls exposed (78.6%), the odds ratio (OR) = 3.81, r = ratio of cases to controls (1:2), Zβ = 80%, Zα/2 = 1.96, p⁻ = (P1 + r × P2)/(r + 1), and q⁻ = 1–p⁻.

All five affected kebeles—Korile, Dembel, Gumtameli, Sekoyta, and Galimeda—were purposefully selected for the investigation. To describe the SAM outbreak by person, place, and time, we utilized the entire line list, which included all SAM reports submitted to the Dubti District Health Office during the outbreak period. However, when investigating the factors associated with the SAM outbreak, all SAM cases in the line list were identified and assigned unique identification numbers. SAM-affected children in these kebeles were then selected using a simple random sampling technique from the line list. These children were then traced back to their communities for data collection. Controls—children who did not meet the standard case definition of SAM—were also recruited using a simple random sampling technique from neighbors living in the same residential areas. For every SAM-affected child, two neighbor controls were recruited.

A SAM outbreak occurs when the number of SAM cases exceed the threshold during a normal season in a specific area. The WHO recommends various threshold calculation techniques for weekly reportable diseases, such as the 75th percentile, mean + 2 SDs, cumulative sum, and a constant case count (22). Considering that Dubti District is an area endemic for child undernutrition, we used the mean + 2 SD method, which adds 2 SDs to the average number of reported SAM cases over the past 5 years. Using District Health Information Software, the current data (2021/2022) were compared to the average weekly SAM reports from 2017 to 2021 to determine whether the action threshold was surpassed.

We used a structured questionnaire adapted from the literature (19, 21, 23–27) and conducted a house-to-house survey to collect data from mothers/caregivers through face-to-face interviews, immunization cards, and anthropometric measurements. The child’s age was estimated using an immunization card, a birth certificate, or information recalled by the mothers or caregivers. Dietary diversity was assessed through 24-h food recall of seven WHO-recommended food items.

Dietary diversity was assessed using the dietary diversity score (DDS) based on 24-h food recall, in accordance with the WHO’s minimum dietary diversity recommendations. A child was considered to have a diversified diet if they consumed four or more food items from the following seven WHO-recommended food groups: (1) grains, roots, and tubers; (2) legumes and nuts; (3) dairy products, such as milk, yogurt, and cheese; (4) flesh foods, including meat, fish, poultry, and liver/organ meats; (5) eggs; (6) vitamin A-rich fruits and vegetables; and (7) other fruits and vegetables. A DDS of ≥4 was considered indicative of a diversified diet (26).

Household food security was measured using the Household Food Insecurity Access Scale (HFIAS). The HFIAS consists of two types of related questions: nine occurrence questions that ask about experiences of food insecurity in the past 4 weeks (30 days) and 9 severity questions that inquire about the frequency of these experiences. Furthermore, the HFIAS categorizes household food insecurity into four categories: category one, food security if [(Q1a = 0 or Q1a = 1) and Q2 = 0 and Q3 = 0 and Q4 = 0 and Q5 = 0 and Q6 = 0 and Q7 = 0 and Q8 = 0 and Q9 = 0]; category two, mildly food insecure access if [(Q1a = 2 or Q1a = 3 or Q2a = 1 or Q2a = 2 or Q2a = 3 or Q3a = 1 or Q4a = 1) and Q5 = 0 and Q6 = 0 and Q7 = 0 and Q8 = 0 and Q9 = 0]; category three, moderately food insecure access if [(Q3a = 2 or Q3a = 3 or Q4a = 2 or Q4a = 3 or Q5a = 1 or Q5a = 2 or Q6a = 1 or Q6a = 2) and Q7 = 0 and Q8 = 0 and Q9 = 0]; and category four, severely food insecure access if [Q5a = 3 or Q6a = 3 or Q7a = 1 or Q7a = 2 or Q7a = 3 or Q8a = 1 or Q8a = 2 or Q8a = 3 or Q9a = 1 or Q9a = 2 or Q9a = 3], as described in detail in the HFIAS (24). Households in category 1, with an HFIAS score of 0–1, were considered food secure, whereas those in categories two, three, or four were classified as food insecure (27).

The child’s vaccination status was assessed using an immunization card and information recalled by the mothers. A child who received all of the vaccines recommended for their age was considered fully immunized (28). A child who presented with a cough, fast breathing, and/or danger signs, based on the integrated management of newborn and child illness classification, was diagnosed with pneumonia (29). Furthermore, diarrhea was defined as passing three or more loose or liquid stools per day (30). Five nurses with a Bachelor of Science degree who had experience in under-five nutritional surveys and two supervisors with a master’s degree in Public Health participated in the data collection.

The control children underwent standardized anthropometric measurements. Briefly, weight was recorded using a calibrated portable scale to the nearest 0.1 kg, with participants wearing light clothing. Height was measured with a calibrated portable stadiometer to the nearest 0.1 cm. The participants stood without shoes, in a Frankfurt position, with their heels, buttocks, shoulders, and heads touching a vertical support. For the children aged 6–23 months, recumbent length was measured. The mid-upper arm circumference (MUAC) was determined by measuring the circumference of the upper arm at its midpoint, with the arm bent at a right angle (20).

We used the English version of the questionnaire, which was translated into the local language, Afarigna, and then back into English. The questionnaire was pretested with 5% of the sample to ensure clarity, completeness, and consistency. Anthropometric indices were measured and interpreted according to the WHO 2006 growth standards (20). The data collectors received 3 days of training on the data collection tool and procedure, as well as on protecting data confidentiality.

The data were entered into EpiData software version 3.1 and analyzed using SPSS software version 25.0. A chi-squared test was conducted to assess differences in the baseline sociodemographic and economic characteristics of the cases and controls. However, when the conditions for the chi-squared test were violated—specifically, when the expected values in at least 80% of the cells were less than five or when any cell had an expected value less than one—Fisher’s exact test was conducted. A binary logistic regression (LR) analysis model was applied to identify risk factors for SAM. Variables with corresponding p-values <0.25 in the bivariable binary LR analysis were further analyzed. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were calculated, and a p-value of <0.05 was considered statistically significant. The overall model fit was assessed using the Hosmer–Lemeshow goodness-of-fit test, with a p-value of >0.05. In addition, the data were assessed for collinearity with a variance inflation factor of less than 5.

Ethical clearance was obtained from the Afar Public Health Institute, ethical approval number APH015/2022. Informed consent was obtained from all individual participants included in the study. The data confidentiality was assured via the de-identification of personal identifier information and the storage of the file in a secure folder. Children who met the case definition of SAM during control selection were linked to nearby health facilities for nutritional intervention.

A total of 260 (58.9%) cases were reported from Galimeda, followed by Korile with 59 cases (13.3%) and Debel with 45 cases (10.2%). Similarly, the highest AR was observed in Galimeda (350/1,000 population), followed by Korile (309/1,000 population) and Debel (300/1,000 population; Table 2).

Using the mean + 2 SDs method, it was found that the threshold level was surpassed from epidemiological week (Epi-week) 45 in 2021 to Epi-week 17 in 2022, confirming the SAM outbreak (Figure 1).

The SAM outbreak began in Epi-week 45 in 2021 and continued through Epi-week 5 in 2022, when it dropped below the action threshold level in Epi-week 17 in 2022. The epidemic curve suggested a continuous common-source type of outbreak (Figure 2).

Breastfeeding was initiated within 1 h of delivery for 67 (79.8%) of the cases and 138 (82.1%) of the controls. During the first 6 months of life, 55 (65.8%) of the cases and 108 (64.3%) of the controls were fed only breast milk. In addition, 33 (35.7%) of the cases and 111 (66%) of the controls received more than four feeds per day (Table 6).

A total of 19 (22.6%) of the cases and 93(55.4%) of the controls were fully immunized for their age. Furthermore, 60 (71.4%) of the cases and 53 (31.5%) of the controls had diarrhea, while 54 (64.3%) of the cases and 53 (31.5%) of the controls had acquired pneumonia (Table 6).

A total of 34 (40.5%) of the households in the case group and 84 (50%) of the households in the control group reported having access to safe drinking water. Similarly, 37 (45%) of the households in the case group and 119 (70.8%) of the households in the control group reported access to sanitation and hygiene (Table 6).

After controlling for potential confounding factors, the children in families with more than five members had 3.34 times greater odds of experiencing SAM compared to the children in smaller families (AOR = 3.34, 95% CI: 1.475−7.563). Similarly, households with more than five under-five children had 4.4 times greater odds of SAM than their counterparts (AOR = 4.44, 95% CI: 2.000−9.866). Compared to the fully vaccinated children, unvaccinated children were 3.6 times more likely to experience SAM (AOR = 3.64, 95% CI: 1.618 ~ 8.198). The children with a history of pneumonia had a 5.6-fold greater risk of experiencing SAM (AOR = 5.61, 95% CI: 2.488−12.651), while those with diarrheal disease had a 4.7-fold greater chance of experiencing SAM (AOR = 4.68, 95% CI: 2.169−10.097; Table 7).

Future research could delve deeper into the relationship between the family income/wealth index and SAM. In addition, investigating the specific child vaccines that were missed and their potential association with SAM would provide valuable insights for targeted interventions. Finally, future research should aim to conduct longitudinal studies to establish more definitive causal relationships between SAM and pneumonia, as well as SAM and diarrhea. By exploring these areas, researchers can contribute to a more comprehensive understanding of the factors contributing to SAM and develop more effective prevention and treatment strategies.