-->PONE-D-25-19278-->-->Pooled prevalence and  Multimorbidity of diarrhea and wasting and its associated factors among children aged 6-24 months in East Africa: Insight from Recent Demographic Health Survey:  A Multilevel analysis-->-->PLOS One

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Reviewer #1: Partly

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: This manuscript addresses an important and timely topic by analyzing the diarrhea and wasting among young children in East Africa using Demographic and Health Survey (DHS) data. The authors aim to estimate the pooled prevalence of this co-occurrence and identify associated factors through multilevel analysis. While the study’s focus is relevant for public health and nutrition policy in low-income settings, several conceptual, methodological, and reporting issues reduce the clarity, coherence, and scientific rigor of the manuscript. The following comments aim to provide constructive suggestions for improving the theoretical framing, variable and model explanation, and interpretation of results.

Introduction

Definition of multimorbidity

The central conceptual framework of the manuscript is problematic. The authors repeatedly frame the co-occurrence of diarrhea and wasting as a form of “multimorbidity.” However, this interpretation does not align with standard definitions in the literature, which describe multimorbidity as the co-existence of multiple chronic conditions within the same individual, typically requiring long-term care or management. Diarrhea, as it is defined a in this study, reflects an acute condition in children. Wasting is referred to as "acute malnutrition", implying a condition with clear short-term or recent onset. However, later in the text, wasting is defined as "a weight-for-height ratio more than two standard deviations below the mean for the reference population", which does not convey any temporal dimension and creates a conceptual inconsistency. Change the study as an investigation of co-occurring entities or syndemic vulnerabilities would be conceptually more accurate and scientifically defensible. the use of “multimorbidity” is misleading and weakens the study’s coherence.

Also, the manuscript lacks consistency in the use of terminology when referring to the co-occurrence of diarrhea and wasting. The authors use multiple labels—“DW,” “DWM,” “DW multimorbidity,” “diarrhea and wasting multimorbidity”— and this leads to confusion about whether “DW” is meant to represent: a descriptive epidemiological finding (as the co-occurrence of two distinct conditions), a new conceptualized clinical entity, a binary variable in the statistical model, or a form of “multimorbidity” in the traditional sense (which would be incorrect, as previously noted).

First, the manuscript should explain if DW is treated as a clinical concept, an analytic outcome, or both. Also, it should define how “DW” is constructed as a variable, using a consistent acronym and label.

Methods

Inclusion and exclusion criteria

The manuscript fails to report the inclusion and exclusion criteria used in the final analytic sample of 78,962 children. It is unclear if children without anthropometric measurements or recent diarrhea data were excluded, if implausible anthropometric values were removed, if the sample includes all children in the age range or only those with complete data… It is recommended that the authors provide a transparent flow of case inclusion (preferably as a diagram), explicitly defining all exclusion criteria and justify the final sample size in the context of the original population.

In line with this, the manuscript provides no information on how missing data were handled, either for the primary outcome (DW) or for covariates. This is an important omission. The authors should quantify the proportion of missing data for each variable used, explain the strategy chosen to manage missing values and justify the approach.

Selected variables

Although the manuscript explains the derivation of some constructed variables (media exposure, birth weight), it remains unclear how other independent variables were operationalized. The authors should explicitly state if these variables were used in their original DHS format or additional recoding was applied.

Analytic approach

The afirmation “this structure could violate the assumptions of independence of observations and equal variance inherent in traditional logistic regression models” is conceptually confused and is not a valid justification for the choice of multilevel modeling, since concerns regarding independence and variance assumptions are already addressed through the survey design correction applied via the svy commands.

The authors employed a multilevel mixed-effects binary logistic regression model to estimate the association between child-level and community-level factors and the likelihood of co-occurring diarrhea and wasting (“DW”). Multilevel modeling should be justified based on theoretical grounds and the need to model between-cluster variability explicitly. this choice could be appropriate given the aim of the study and the hierarchical nature of DHS data.

Results

The results section presents some weaknesses in reporting, interpretation and clarity.

Table 1 presents several issues that limit its clarity and interpretability. First, the total number of children included in the analysis is not reported, which is essential to contextualize the percentages. Some units of measurement for variables are not clearly indicated. Additionally, for dichotomous variables, it would improve readability to report only one category to avoid redundancy (“Child sex”,”Mother ocupation”…).

It would be helpful to report the prevalence of diarrhea and malnutrition separately, in addition to the joint outcome (DW), as this would offer greater epidemiological context and comparability with prior studies.

The interpretation of the MOR could be clarified. First, the use of the term "significant variation" could be misinterpreted in a statistical sense. To avoid ambiguity, it would be clearer to use terms such as "substantial" or "considerable" variation when interpreting the MOR. The MOR does not compare children in areas of "high vs. low prevalence", but rather quantifies the median increase in odds when comparing two children with identical characteristics from two randomly selected countries. A MOR of 2.39 reflects substantial between-country heterogeneity. A decrease in the MOR from the null model to Model III actually indicates that the model explains more, not less, of the between-cluster variability in the outcome.

The AOR for rural residence of 0.85 is inaccurately described as a 20% reduction, when it actually represents a 15% lower odds of DW. Also, there appears to be a formatting or numerical error in the reporting of the adjusted odds ratio for “Secondary” in mother education status: the AOR is reported as 1.46, but the 95% confidence interval is 1.49–3.03, which is inconsistent.

The use of a forest plot typically implies that independent estimates ( from different studies or settings) are being synthesized, often using meta-analytic methods. That is clearly not the case here.The plot assigns equal weights (9.1%) to each country, despite substantial differences in sample sizes and it is not well explained what the plotted values reflect. If the intention was to display variation in prevalence across countries, alternative formats such as geographical maps would be more appropriate and transparent. At a minimum, the figure should be accompanied by a clear methodological explanation.

Discussion

Some changes are needed to improve the clarity of the discussion.The beginning of the discussion repeat the study aim and results with little interpretive value.

The authors report a weighted pooled prevalence of diarrhea and wasting multimorbidity (DW) of 9% among children aged 6–24 months in East Africa and cite references 22 and 23 to support the significance of this burden. However, upon closer examination, these references pertain to studies on breastfeeding practices , not to the prevalence of diarrhea, wasting, or their co-occurrence. This makes them inappropriate citations in this context.

Additionally, while references 16 and 31 (Demissie et al., 2021; Tareke et al., 2022) do report on the prevalence of diarrhea alone in sub-Saharan and East African children (approximately 14–16%), they do not assess the joint occurrence of diarrhea and wasting. These sources cannot be used to validate or compare the DW prevalence reported in the current study.

The finding that younger maternal age (15–24 and 25–34 years) is associated with significantly lower odds of DW compared to older mothers (35–49 years) appears counterintuitive, especially considering previous literature suggesting that young maternal age is a risk factor for child undernutrition and illness (e.g., refs 16, 29). However, this result may be influenced by several underlying factors that are not adequately explored in the discussion.

It would strengthen the study to explore whether the effect of maternal age persists when stratifying by key mediating factors (maternal education, household wealth, access to care...)

It also happens with the association between rural residence and lower DW risk. It contradicts many prior studies. The proposed explanation (“more extended breastfeeding and community support”) is not enough substantiated with evidence.

While the study provides valuable insights, it may be worth reconsidering the selection and operationalization of some key variables. For instance, breastfeeding is only captured through the timing of initiation within the first hour of birth. As i know, DHS offers additional indicators such as exclusive breastfeeding duration, continued breastfeeding at 1 and 2 years, etc. which are strongly associated with both diarrhea and malnutrition.

Differences between countries (Malawi and Zimbabwe) are just mentioned .The authors selected a multilevel modeling approach that includes country but this choice is not matched by a sufficiently robust analytical or interpretative emphasis on country-level differences.

There is no enough consideration of potential macro-level determinants such as differences in health system infrastructure, national nutrition or vaccination programs, water and sanitation policies, or socioeconomic indicators. The authors could include a brief summary of key contextual differences between countries with notably high/low DW prevalence and discuss possible structural or policy-level explanations for these differences (using DHS data or relevant literature).

Grammatical, typographical, and syntactic errors

The manuscript contains grammatical, typographical, and syntactic errors. for example: “This studyis based...” “Children who were breastfeed...” “among children age from 6–24months” “included in to multivariable analysis”. Also, some variable labels are misspelled: “laterine” , “Media accesses” , “birth weight small”… These errors hinder readability. A language revision by an english speaker or professional editor with experience in academic writing is recommended.

General conclusions

The main issue with this article lies in its conceptual framework, which is fundamentally flawed. The outcome variable combines an acute infectious disease (diarrhea) with a non-acute condition (wasting) under the label of multimorbidity. This does not align with standard definitions of multimorbidity in the literature and undermines the theoretical coherence of the study.

The use of multilevel modeling is, in principle, an appropriate analytic strategy. However, if the model is designed to account for between-country variability, the manuscript should include a substantial section that compares and interprets the results across countries with detail. This aspect is largely underdeveloped.

The article also fails to describe how missing data were handled or what inclusion and exclusion criteria were applied in the final analytic sample.

In addition, the manuscript contains several minor issues—including grammatical and typographical errors, inconsistencies in variable labeling, and occasional formatting problems in tables. Moreover, the presentation of the results is suboptimal, with incomplete descriptive statistics, unclear figure and insufficient explanation of key tables and variables. these issues are relatively easy to correct , they remain secondary to the more fundamental concerns regarding the study’s conceptual framework and outcome definition.

Reviewer #2: There is need to be consistent with abbreviations, DW is used sometimes and DVM is used some other time.; line 36 and line 48

So many Typos and formatting errors that needs to be corrected: Line 96; ‘Photogenes’ Do you mean pathogens? Line 106 Severe not sever

Method:

Data source :‘This study is based on most recent DHS conducted after 2016 appears vague, specify exact survey years for each country to improve transparency.

Line 142: DHS definition of diarrhea (two-week recall) may introduce recall bias; please acknowledge this limitation.

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Reviewer #1: Yes: Alicia Serrano de la Cruz

Reviewer #2: Yes: Elizabeth Adedire

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<p>Pooled prevalence and co-occurrence of diarrhea and wasting and its associated factors among children aged 6-24 months in East Africa: Insight from Recent Demographic Health Survey:  A Multilevel analysis

PONE-D-25-19278R1

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Kind regards,

Edison Arwanire Mworozi, M.D

Academic Editor

PLOS One

Language and Formatting: Despite proofreading, some minor typographical errors and formatting inconsistencies remain (e.g., "studyis" and "laterine").

Abstract Length: The abstract is slightly lengthy and could be more concise to align with journal standards.

Repetition in Discussion: While the authors addressed the repetitive opening, some parts of the discussion still reiterate findings without adding interpretive value.

Clarity in Results: Some sections of the results could be streamlined for better readability, especially when discussing statistical measures.