Integrating Socio-Demographic and Local Sustainability Indicators: Implications for Urban Health and Children’s Vulnerability in Henequén Neighborhood in Cartagena, Colombia

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study investigates the socio-demographic conditions and local sustainability indicators in the Henequén neighborhood, a former landfill site in Cartagena, Colombia, and their implications for public health and social vulnerability, particularly among children. The study if of significance in terms of study case application and sustainability. The following issues need to be addressed before consider for publication. 

1. please improve the quaility of the charts and maps. 
2. please add a discussion scetion to illustrate the contribution to area of study and limitations
3. Providing more detail on how the "Local indicator" values were calculated from the survey data.
4.  Expanding on specific, actionable, and potentially policy-relevant recommendations based on the key findings would increase the manuscript's impact. 

Author Response

Evaluator 1 Comments and Suggestions for Authors

The study investigates the socio-demographic conditions and local sustainability indicators in the Henequén neighborhood, a former landfill site in Cartagena, Colombia, and their implications for public health and social vulnerability, particularly among children. The study is of significance in terms of study case application and sustainability. The following issues need to be addressed before considering for publication. 

Comments 1. “Please improve the quality of the charts and maps.” 

Response 1: We appreciate the reviewer’s emphasis on clarity of visual materials. In the revised manuscript, Figures 3, 4, and 5, have been re-exported as high-resolution, vectorial graphics (SVG ≥ 300 dpi) to eliminate pixelation. The map (Figure 1) is already made in SVG format.


Comments 2. “Please add a discussion section to illustrate the contribution to the area of study and limitations”. 

Response 2: Thank you for this recommendation. We improved the discussion section by adding a paragraph (lines 189 to 194) and adding the contribution and the study's limitations in lines 511 - 134. This discussion has been included in the manuscript to strengthen its scientific rigor and relevance to the design of public policies in urban health and territorial planning with a focus on equity. 


Comments 3. Providing more detail on how the "Local indicator" values were calculated from the survey data.

Response 3. We appreciate your request for greater clarity in calculating the "Local Indicator" values. We have added a paragraph in the Methods section that describes the procedure in detail: Addition of paragraph (lines 182-199).

Comments 4. Expanding on specific, actionable, and potentially policy-relevant recommendations based on the key findings would increase the manuscript's impact. 

Response 4. We appreciate your suggestion and have added a subsection to the Conclusions and Recommendations section detailing specific, feasible, and high-impact actions to mitigate socioenvironmental vulnerability in Henequén (Lines 568 - 600).

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

This is a compelling manuscript which ties a specific community to a localized lack of progress attaining the relevant SDGs. The environmental and humanitarian aspects surrounding the social and economic conditions, and their impact on public health, especially of children, in Henequen are well organized and described. Furthermore, the correlational study is well presented in the context of the variables of interest. There are opportunities to strengthen the manuscript, as issues of reproduction to not appear to be adequately integrated into the analysis. I point those out as comments in the attachment. Figures 4 and 5 need to be more descriptive, for without labeling the variables other than F, V, and SE, the figures make no sense to your readers.   

Comments for author File: Comments.pdf

Author Response

Evaluator 2 Comments and Suggestions for Authors

Comments 1: This is a compelling manuscript which ties a specific community to a localized lack of progress attaining the relevant SDGs. The environmental and humanitarian aspects surrounding the social and economic conditions, and their impact on public health, especially of children, in Henequen are well organized and described. Furthermore, the correlational study is well presented in the context of the variables of interest. There are opportunities to strengthen the manuscript, as issues of reproduction to not appear to be adequately integrated into the analysis. I point those out as comments in the attachment. Figures 4 and 5 need to be more descriptive, for without labeling the variables other than F, V, and SE, the figures make no sense to your readers.   

Response 1: We deeply appreciate your comments and understand the concern about the clarity of the figures. After careful consideration, we have decided to maintain the original coding of the variables (F, V, and SE) in Figures 4 and 5 for the following reasons: Visual economy and readability: Multiple Correspondence Analysis presentations often include dozens of variables. Replacing each code with the full name would make the graphs excessively dense and complicate the spatial interpretation of the associations between variables. Methodological consistency: The use of short codes for dimensions and variables is standard in multivariate studies in psychometrics and social sciences and facilitates comparison with previous studies that use similar abbreviations. Editorial space: In the Urban Science format, figures should be kept at a size that ensures visibility in print and digital formats. Long labels could reduce the point size and compromise graphic quality.

However, we have incorporated detailed legends and explanatory text in the figure captions to ensure that any reader can correctly interpret each element (Figure 4: 463-468).

 

Reviewer 3 Report

Comments and Suggestions for Authors

Review report

The authors are commended for tackling an important and timely issue concerning urban vulnerability and SDG integration in marginalized communities. The focus on Henequén adds a potentially valuable case to the discourse on inclusive urban development. However, the manuscript has several conceptual and methodological shortcomings that must be addressed before it can be considered for publication.

• The introduction outlines challenges of urbanization in Henequén but lacks clarity in defining the specific research problem and fails to identify a clear gap. The critique of top-down SDG applications is generic and unsupported by prior studies.
• The proposed framework integrating socio-demographic and sustainability indicators is vaguely described. It’s unclear whether it is theoretical, methodological, or practical, and how it differs from existing tools. The contribution lacks specificity and novelty, especially without addressing known methodological or conceptual limitations.
• The methodology section raises concerns. The sample of 158 families lacks information on selection criteria and justification, with no detail on survey administration—raising potential biases. The study uses a cross-sectional, correlational design but draws causal inferences without acknowledging its limitations. No reliability metrics are reported for the instrument.
• The exclusive use of quantitative data limits insight into complex issues like child vulnerability. The absence of qualitative methods weakens the analysis. MCA and ANOVA are used, but the MCA explains only 8% of variance, suggesting poor data capture. Higher dimensions are ignored without justification. The comparison to national SDG targets lacks methodological rigor, risking misrepresentation.
• Some results are unclear or questionable—e.g., the wide abortion rate range, unexplained child mortality figures, and the unusually low rate of substance use, which may reflect social desirability bias.
• The MCA highlights some variables, but given the low explained variance, their significance is doubtful. The discussion is repetitive and shallow, often restating survey results without deeper interpretation.
• Causal claims (e.g., linking overcrowding to health issues) are unsupported by data specific to Henequén. The conclusion is vague, lacking concrete interventions or prioritization of issues. It omits discussion of methodological and data limitations and overstates the framework’s value, which is neither well-defined nor illustrated.

Overall, the article has major conceptual and methodological flaws that needs substantial revisions.

 

Author Response

Evaluator 3 Review report

Comments 1: The authors are commended for tackling an important and timely issue concerning urban vulnerability and SDG integration in marginalized communities. The focus on Henequén adds a potentially valuable case to the discourse on inclusive urban development. However, the manuscript has several conceptual and methodological shortcomings that must be addressed before it can be considered for publication. The introduction outlines challenges of urbanization in Henequén but lacks clarity in defining the specific research problem and fails to identify a clear gap. The critique of top-down SDG applications is generic and unsupported by prior studies.

Response 1. We appreciate your comments and have strengthened the Introduction to clarify the research question and support the critique of the top-down approach to the SDGs with previous studies. “Precise definition of the problem and knowledge gap”. We have added a sentence at the end of the second paragraph that establishes our objective (Lines 72-78). This demonstrates that the problem is not only generic urban vulnerability, but also the integration of SDGs at the post-landfill neighborhood level, a topic not yet covered by research in Latin America. We also added lines 86 - 91. With these changes, the Introduction now clearly defines the scoped problem of local SDG implementation in post‐landfill neighborhoods, identifies the research gap created by the lack of studies on such contexts in the regional literature, and justifies the critique of the top‐down SDG approach.

 

Using specialized references, all while explicitly linking this rationale to the research question and the study’s original contribution.

 

Comments 2: The proposed framework integrating socio-demographic and sustainability indicators is vaguely described. It’s unclear whether it is theoretical, methodological, or practical, and how it differs from existing tools. The contribution lacks specificity and novelty, especially without addressing known methodological or conceptual limitations.

Response 2: Thank you for your comment. To enhance the clarity and novelty of our integrative framework, we have introduced in Materials and Methods a paragraph (lines 184-193) and another one in lines 587-596.

 

Comments 3: The methodology section raises concerns. The sample of 158 families lacks information on selection criteria and justification, with no detail on survey administration—raising potential biases. The study uses a cross-sectional, correlational design but draws causal inferences without acknowledging its limitations. No reliability metrics are reported for the instrument.

 

Response 3: Thank you for your comments. Below we clarify the points you mentioned:

 

Sample Criteria and Justification. Population and Sampling Framework: We describe the study population as all families with children aged 4 to 10 enrolled at the San Francisco de Asís Educational Institution, Henequén (GIS mapping used to delimit the sector).

Inclusion criteria: (a) permanent residence in Henequén; (b) at least one child aged 4–10 enrolled in the school; (c) signature of informed consent by the parent or guardian.

Sampling Strategy: Stratified random sampling by neighborhood area (north, center, and south), with proportional quotas based on the number of enrolled students, ensuring territorial representativeness and minimizing bias due to population concentration.

Survey Administration. Procedure: The survey was administered in person by four trained interviewers (psychologists and social workers) between March and April 2024, using digital forms on tablets to ensure data quality and the recording of GPS coordinates.

Quality Control: A pilot study was conducted with 15 families to adjust wording and detect ambiguities, and weekly field supervisions were implemented to resolve questions and verify compliance with protocols.

Instrument Reliability

After the pilot phase, we calculated Cronbach's alpha for each dimension of the questionnaire:

Family data: α = 0.81

Housing conditions: α = 0.77

Access to services and health status: α = 0.79

These values ​​exceed the threshold of 0.70, indicating acceptable internal consistency.

Acknowledgment of Design Limitations: Addition of paragraph - Lines 585-594.

 

Comments 4. The exclusive use of quantitative data limits insight into complex issues like child vulnerability. The absence of qualitative methods weakens the analysis. MCA and ANOVA are used, but the MCA explains only 8% of variance, suggesting poor data capture. Higher dimensions are ignored without justification. The comparison to national SDG targets lacks methodological rigor, risking misrepresentation.

Response 4:  We appreciate your valuable comments, which have allowed us to critically reflect on the approach and scope of the study. Exclusively Quantitative Approach: We recognize that child vulnerability involves complex dimensions that could benefit from qualitative methodologies. However, the objective of this study was to construct a quantifiable baseline to assess local achievement of selected SDG targets in a specific urban community, using data comparable with official sources. As mentioned in the Discussion, we suggest that future phases of the project incorporate participatory qualitative methodologies (focus groups, interviews with caregivers and children) that complement this initial approach and allow for a deeper understanding of family experiences, perceptions, and trajectories.

Justification for the Use of MCA and Factorial Dimensions: In the case of Multiple Correspondence Analysis (MCA), it is true that the first factorial dimension explains 8.3% of the total inertia, which may seem limited. However, as clarified in the Results section, this value is consistent with similar studies using multiple categorical variables with high dispersion. In exploratory multivariate analyses such as MCA, foregrounds do not necessarily capture a large proportion of the total variance, but they do reveal interpretable association structures between dimensions. Furthermore, a methodological note has been added justifying why visualization in two dimensions (planes I and II) is prioritized, given their greater interpretive value for communicative purposes. We also clarify that additional planes were explored (dimensions III and IV), whose patterns did not provide new relevant information and were therefore omitted for visual economy.

 

Comments 5. Some results are unclear or questionable—e.g., the wide abortion rate range, unexplained child mortality figures, and the unusually low rate of substance use, which may reflect social desirability bias.

Response 5: We appreciate your comment and understand your concern regarding certain results that, at first glance, may seem unusual. However, we believe that these findings validly reflect the particularities of the sociodemographic and emotional context of the population studied.

First, regarding the reported abortion rate, we recognize that the range may seem broad, but it is consistent with the reality of a community affected by multiple forms of structural violence, including sexual violence, a lack of accessible reproductive health services, and high economic precariousness. In this environment, reproductive decisions are not always planned or safe, which translates into significant variability among families. The data collected were reported with sensitivity and confidentiality, and were mostly reported by women heads of household, many of whom have lived through traumatic experiences that affect both their reproductive health and their willingness to talk about it.

Regarding the infant mortality figures, these were collected through direct questions and correspond to events that occurred within the family unit (deceased children, not deaths of minors in general). Therefore, they should not be interpreted as population rates but rather as indicators of the real impact of living conditions on specific families.

Regarding the underreporting of psychoactive substance use, we have considered the possibility of social desirability bias, as you mention. However, it is important to understand that in this community, there is a strong social censure toward use, especially when there are children in the home. Many families explicitly express a desire to protect minors, and although use may occur in some cases, it tends to be hidden or denied during interviews for fear of stigmatization or sanctions. Furthermore, use is usually more associated with young men outside the caregiving role, so it is plausible that in a sample focused on mothers and female heads of household, the prevalence is indeed low.

 

Comments 6. The MCA highlights some variables, but given the low explained variance, their significance is doubtful. The discussion is repetitive and shallow, often restating survey results without deeper interpretation.

 

Response 6. We appreciate your comments on the interpretation of the Multiple Correspondence Analysis (MCA) and the in-depth discussion. In the revised version of the manuscript, we have addressed both concerns as follows:

 

First, regarding the low variance explained in the MCA, we acknowledge that the first factorial plane captures only 8.3% of the total inertia, which may seem limited. However, as noted in the new methodological note in the Results section, this value is common in studies that analyze multiple, dispersed categorical variables, such as the sociodemographic and housing conditions considered here. In the MCA, the relevance lies not only in the percentage of variance, but in the coherence and stability of the observed groupings. In this sense, the analysis allows us to identify structural patterns of association—for example, the coincidence between overcrowding, precarious housing, female head of household, and low educational level—that enrich the understanding of compound vulnerability.

Second, to respond to your comment on the discussion, we have rewritten and reorganized this section to avoid repetition and provide a more in-depth interpretive reading of the findings. Rather than simply repeating results, they are now contextualized within relevant conceptual frameworks (social determinants of health, environmental justice, differential approaches to childhood), and their implications for the design of inclusive urban public policies are discussed. Furthermore, some findings are contrasted with similar studies in marginalized neighborhoods in Latin America, which allows Henequén to be situated within a regional urban context.

With these modifications, we believe the use of the MCA is justified and that the discussion now serves a more solid analytical and propositional function, better articulating the results with the conceptual framework and with concrete implications for decision-making. We deeply appreciate your contributions, which allowed us to strengthen the interpretive quality of the manuscript.

 

Comments 7. Causal claims (e.g., linking overcrowding to health issues) are unsupported by data specific to Henequén. The conclusion is vague, lacking concrete interventions or prioritization of issues. It omits discussion of methodological and data limitations and overstates the framework’s value, which is neither well-defined nor illustrated.

Response 7. We appreciate your comments on the interpretation of the Multiple Correspondence Analysis (MCA) and the in-depth discussion. Additionally, we included several paragraphs to the discussion, trying to clarify the evaluator's questions.

Regarding the low variance explained in the MCA, we acknowledge that the first factorial plane captures only 8.3% of the total inertia, which may seem limited. However, as noted in the new methodological note in the Results section, this value is common in studies that analyze multiple, dispersed categorical variables, such as the sociodemographic and housing conditions considered here. In the MCA, relevance lies not only in the percentage of variation, but also in the coherence and stability of the observed groupings. In this sense, the analysis allows us to identify structural patterns of association—for example, the coincidence between overcrowding, precarious housing, female head of household, and low educational level—that enrich the understanding of compound vulnerability.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thanks for the revision.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have addressed the majority of my comments and suggestions, and the paper now appears ready for publication.