Introduction

Acute malnutrition, also known as wasting, occurs when a child’s nutritional status rapidly deteriorates, causing them to become too thin for their height due to poor nutrient intake and/or disease. Weight-for-height, mid-upper arm circumference (MUAC), and nutritional edema are used to define wasting [1]. The two forms of wasting are severe acute malnutrition (SAM) and moderate acute malnutrition (MAM). Global acute malnutrition (GAM) refers to the combination of MAM and SAM and is often used to measure nutritional status at the population level, indicating the severity of an emergency [2].

The introduction of the Community Therapeutic (CTC) and the subsequent Community-based Management of Acute Malnutrition (CMAM) in the late nineties had a significant impact on the humanitarian sector [3,4]. These innovations were designed to be delivered in emergency contexts, and UNICEF was responsible for providing outpatient care for uncomplicated SAM, which included the distribution of ready-to-use therapeutic food (RUTF). The World Food Programme (WFP) was responsible for implementing targeted supplementary feeding programs (TSFPs) for MAM [5].

As the primary United Nations health regulatory organization, the World Health Organization (WHO) has historically been responsible for addressing the needs of children with SAM. As the WHO provides guidance specifically for the treatment of SAM, the focus is primarily on complicated SAM cases. Prioritizing children at the greatest risk of mortality, the CMAM approach initially focused on treating SAM, as children with SAM have a 9–12 times higher risk of death than well-nourished children [6], as evidenced by the 2007 joint United Nations statement on community-based SAM management [7]. Since then, there has been a significant push, mainly led by UNICEF, to implement community-based SAM treatment within existing healthcare systems. Consequently, the treatment model for outpatient SAM management has continued to evolve. Unfortunately, this progress has not been matched by an equal focus on scaling up the supplementation and prevention of MAM [8]. Thus, the current study assessed the readiness of health posts to provide services for children with SAM and MAM.

Ethiopia was one of the first countries to pilot the CMAM model in the early 2000s. The country has since embarked on a massive roll-out of the CMAM Program in the HEP [9], which is now delivered in over 18,000 facilities [10]. HEP has enabled Ethiopia to achieve significant improvements in maternal and child health and prevent child death through timely admission and treatment of wasting [11].

Since 2020, the CMAM community has focused on simplifying CMAM to expand coverage by testing MUAC-based and combined protocols, such as ComPAS and OptiMA, which have shown non-inferior recovery compared with standard protocols [12,13]. Operational studies have reported promising gains from these simplified models but have also highlighted persistent challenges, including relapse and retention, limited reach in remote and pastoral areas, and supply chain constraints [14,15]. To address these operational gaps and validate effectiveness at scale, ongoing trials in Ethiopia are testing optimized dosages and delivery approaches [16].

The extent to which a country’s healthcare system can handle the management of wasting is a crucial factor in maintaining continuity of care [8]. Over the last 13 years (2008–2020), UNICEF has made significant progress in strengthening health systems and integrating SAM treatment into Ethiopia’s primary healthcare, resulting in an estimated 3.6 million SAM children being enrolled in the CMAM program [10]. However, there were no similar goals for the management of MAM until August 2019, when the Ministry of Health (MoH) released a new National Guideline for the Management of Acute Malnutrition, which integrated MAM management into the Ethiopian healthcare system [17]. Prior to 2019, the National Disaster Risk Management Commission (NDRMC) oversaw the management of MAM and TSFP with the support of the WFP, providing monthly food rations based on screenings conducted by Health Extension Workers (HEWs) [18].

Integrating the Management of MAM into primary healthcare has the potential to increase the caseload, which could compromise the care provided to SAM children and thereby further stretch already limited resources. Therefore, it is crucial to determine to what extent health posts in pilot IMAM districts prepared to manage SAM and MAM. Therefore, knowing the readiness of health posts to provide both SAM and MAM services will support improvements in services and guide the design and implementation of strategies to enhance the quality of care provided.

Methods

Index creation

A composite index is developed using a weighted additive approach. The weighted additive index was created by summing the elements and considering the indicator counts within each domain. This process included adding the indicators in each domain, dividing the sum within each domain by the number of indicators in that specific domain (Table 1), multiplying by 100, and finally dividing by the total number of domains within the index. Previous research has demonstrated that employing three different techniques, simple additive, weighted additive, or principal component analysis, to compute quality indices typically yields results that are generally consistent [22]. The weighted additive method is recommended owing to its simplicity of calculation and interpretation [23].

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Table 1. Summary of domains and indicators used to create indices for readiness.

https://doi.org/10.1371/journal.pone.0320824.t001

Result

Availability and readiness

The readiness assessment showed varying levels of preparedness across service domains for SAM and MAM management (Table 2). For basic amenities, the weighted score was 45.8% for both SAM and MAM, driven largely by the low availability of electricity (40.3%) and limited access to improved water sources (51.4%).

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Table 2. Availability of items and readiness for SAM and MAM management.

https://doi.org/10.1371/journal.pone.0320824.t002

In the staff and guidelines domain, SAM and MAM scored 66.7%. The high coverage of trained staff in the management of acute malnutrition (88.9%) and the availability of registration and follow-up cards (90.3% for SAM; 86.1% for MAM) supported this moderate readiness. However, gaps in growth charts (11.1%) and IYCF counselling aids (47.2%) were observed.

For equipment, the weighted scores were 60.3% for SAM and 64.6% for MAM, with widespread availability of MUAC tapes (97.2%) and child/infant scales (83.3%), however, low availability of timers (16.7%) were observed.

The medicines and commodities domain scored 67.1% for SAM and 69.0% for MAM, supported by the good availability of RUTF/RUSF (79.2% for SAM; 59.7% for MAM), vitamin A capsules (77.8%), and deworming tablets (69.4%). Low availability of antibiotics, zinc, and IFA tablets in SAM services were also observed.

Overall, the average weighted readiness score was 57.9% for SAM and 53.9% for MAM, indicating that SAM services were slightly better prepared. Only 19.4% of facilities met the ≥ 75% readiness threshold for SAM, compared with 11.1% for MAM. Fig 1 illustrates the overall weighted readiness scores for SAM and MAM services across the health facilities. In general, SAM services had a slightly higher median readiness score (55.6%, IQR: 45.8 to 70.5) compared with MAM services (53.2%, IQR: 41.9 to 67.1). A statistically significant difference was observed between SAM and MAM service readiness across facilities (p < 0.001), indicating that readiness for SAM services was higher, although both services exhibited substantial gaps. Table 3 provides detailed descriptive statistics.

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Table 3. Descriptive statistics of readiness according to the type of area and distance from the catchment health.

https://doi.org/10.1371/journal.pone.0320824.t003

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Fig 1. Readiness scores for SAM and MAM services.

https://doi.org/10.1371/journal.pone.0320824.g001

Fig 2 illustrates the differences in service readiness scores between the agrarian and pastoral areas. In pastoral regions, both SAM and MAM services had low levels of readiness, with the median readiness score highest for SAM (median (IQ): 50.9 (40.8 to 80.9)) and MAM (median (IQ): 40.0 (28.6 to 49.5), with a statistically significant difference between SAM and MAM (p < 0.001). in other words, SAM management service is better prepared than MAM services. In agrarian regions, service readiness was higher for both SAM and MAM, with median scores of 61.6 (49.1 to 71.7) for SAM and 60.5 (47.5 to 67.3) for MAM, and statistically significant difference between the readiness levels of the two services (p = 0.047).

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Fig 2. Service readiness according to the type of area.

https://doi.org/10.1371/journal.pone.0320824.g002

Fig 3 presents the differences in the service readiness score according to the health post distance from catchment health centers. Among health posts close to catchment health centers (<20 km), the readiness percentage score was highest for SAM median (IQ): 63.4 (50.3 to 73.5)) at p = 0.043. Both SAM and MAM services have low levels of readiness. Among health posts far from the catchment health posts (>20 km), the service readiness percentage score was highest for SAM (median (IQ): 51.8 (41.1 to 59.2)) at p < 0.001.

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Fig 3. Service readiness according to the distance from the catchment health center.

https://doi.org/10.1371/journal.pone.0320824.g003

Quantile regression model estimates for readiness

Table 4 presents the median and third quantile regression model estimates for readiness for SAM and MAM services. For SAM readiness, neither the area (agrarian and pastoral) nor proximity to the catchment health center significantly influenced readiness. For MAM readiness, agrarian areas were positively associated with higher readiness for MAM (p = 0.040), and readiness was more pronounced in the context of higher levels of readiness (p = 0.02). Furthermore, being closer to the catchment health center was also associated with higher readiness (p = 0.016). However, the effect of proximity is not significant in the context of higher readiness.

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Table 4. Median and third quantile regression model estimates for SAM and MAM readiness.

https://doi.org/10.1371/journal.pone.0320824.t004

Discussion

The readiness assessment showed moderate overall preparedness for wasting services in the health posts surveyed, with notable gaps across domains. Basic amenities scored poorly (45.8% for both SAM and MAM), whereas staff/guidelines and medicines/commodities performed better (66.7% and 67.1% for SAM, 66.7% and 69.0% for MAM, respectively). SAM services were slightly more prepared than MAM services, with overall weighted scores of 57.9% versus 53.9%, and only 19.4% of facilities achieved ≥75% readiness for SAM compared with 11.1% for MAM. These findings align with the evidence from other low- and middle-income countries that documented infrastructure deficits, irregular supply chains, and uneven workforce capacity as dominant constraints on facility-level malnutrition response [24,26–29].

For example, in Bangladesh, facilities lacked essential anthropometric tools, glucometer, medicines, and therapeutic foods, with inadequate manpower and training being major barriers [28]. Similarly, an assessment in India found deficiencies in helper staff, medical social workers, and emergency equipment, though beneficiaries expressed satisfaction with available services [26]. Mozambique’s health facilities showed poor readiness scores, with nutrition services scoring 57.1% and diarrhea services 72.2%, primarily due to unavailable human resources, guidelines, and training [24].

The notably low score for basic amenities (electricity and water) mirrors multi-country analyses that identified infrastructure as a recurrent weak link in delivering quality care [27]. This may also be explained by the fact that our study was conducted at lower levels of primary healthcare, health posts in rural areas where facilities often lack essential resources and infrastructure. Similar findings have been reported elsewhere; for example, one study showed that hospitals generally had much better service readiness compared with health centers and clinics [30]. Primary healthcare is a vital source of essential services for underserved populations and has the potential to serve as a powerful platform for addressing a wide range of health challenges in low-income countries [31]. However, this potential can only be realized if greater attention is directed toward strengthening infrastructure and supplies at health posts, which are the first point of care for much of the population, especially in rural areas.

Providing child wasting services requires a reliable supply chain that ensures the availability of essential nutritional products and medicines needed for service delivery. It is crucial to manage SAM and MAM by providing RUTF or RUSF, which depend on the supply chain’s ability to transport these products from central warehouses to individual health facilities. Stockouts can hinder access to care and discourage community members from seeking these services [32]. It is also worth mentioning that some challenges are unique to specialized nutrition products designed to manage wasting in addition to health system limitations, including limited human capacity, infrastructure, and transportation to hard-to-reach regions. It is crucial to consider specific challenges, including the considerable size and volume of the commodity, the unpredictability of demand due to seasonal and emergency-related fluctuations, and the potential for product misuse [33].

Despite the considerable training efforts made by the nutrition partners, the study results indicated that a substantial portion of the health workforce in the study areas had not been trained in the new guideline for managing acute malnutrition, with 12% of the workforce remaining untrained. This lack of training may impair healthcare facilities’ readiness to provide wasting services. Frequently, pre-service and in-service health training curricula lack a nutrition component that includes the significance of wasting management, how to detect wasting, where to refer, and other relevant information. The combination of inadequate training and the limited time that healthcare workers have with each beneficiary contributes to the under prioritization of wasting services [34–36].

Although both SAM and MAM readiness scores were low, we observed a significant difference between the two services, with SAM outperforming the MAM. One possible explanation for this difference is that SAM services have already been integrated into the health system (since 2008), while MAM is still in its early stages of integration into Ethiopian primary health care. While global guidelines for SAM exist and have provided relatively consistent national guidelines, leading to successful integration into health systems [2,37,38], MAM lacks equivalent models for scaling up, including health system integration. As a result, a vacuum has been created, which has been filled by varied national and agency policy guidance and practices, often biased towards humanitarian settings [8,39].

The institutional separation of responsibilities between UNICEF and WFP poses challenges stemming from their respective ways of working. For instance, WFP TSFPs are designed to address GAM levels that exceed 10% or are between 5–9% with exacerbating factors that primarily relate to food security [2,40]. By contrast, UNICEF aims to achieve 100% coverage for SAM treatment, particularly in areas where GAM rates are high and health services are available. It is worth noting that SAM services are provided throughout the year [41], whereas TSFPs may only be delivered during vulnerable periods, which typically span part of the year [40].

Services for MAM tended to be better prepared in agrarian areas than in pastoral regions, although there was no notable disparity in SAM readiness between the two. This could be attributed to the fact that HEP has accomplished better outcomes in agrarian regions since it was initially intended to provide healthcare packages to these areas [11,42], and has since evolved in various ways, including adaptation to pastoral communities [43]. Despite remarkable improvements in health service coverage [44], there are substantial disparities between geographic regions, urban and rural areas, and agrarian and pastoralist settings [45–48].

Health posts located near catchment health centers were better prepared than those located further away. This could be due to the fact that nearby health posts receive more support from the nearby health center, and it is easier for the health centers to provide supervision and other necessary support to the health posts. By collaborating with each other in terms of human resources, supply, finance, and capacity building within the referral network, health facilities can enhance the quality of care, improve patient and staff satisfaction, reduce overall patient costs, and decrease preventable morbidity and mortality by reducing unnecessary referrals [49].

The study was cross-sectional; consequently, the assessment failed to capture readiness over time, which can change depending on logistics, specifically the availability of nutritional commodities at health facilities. However, this study’s methodology can serve as a guide for situational analyses and policy decisions beyond the scope of this cross-sectional study. The study relied on respondents on some questions like training, with limited verification processes. As a result, recall bias may be a limitation, particularly for training questions. For instance, the survey lacked systematic registration or training reports to confirm the answers provided by health professionals. Although several health facilities in six districts across six regions were sampled, generalization was not possible particularly for health centers and hospitals. Nonetheless, we found that SAM and MAM services were unprepared, indicating lower readiness particularly at lower levels of the primary health care system.

In conclusion, the findings point to several priorities. First, strengthening the basic infrastructure at primary-level facilities is foundational and should accompany any expansion of CMAM or MAM integration into the primary health care system. Second, supply chain improvements and routine forecasting/prepositioning of both SAM and MAM commodities are needed for SAM and MAM to be delivered routinely at the health facilities. Third, investments to build MAM capacity through targeted training, and routine supervision are required so that MAM services are properly integrated into primary health care.

Finally, the difference in facility readiness, with some facilities performing well while many remain underprepared, underscores the need for targeted, context-specific interventions rather than one-size-fits-all solutions. Facilities in crisis-affected or remote/pastoral areas will need tailored support like mobile outreach and community-based delivery models.

Acknowledgments

The authors wish to thank the study data collectors and district and health facility staff.