Generalized linear mixed model approach for analyzing water, sanitation, and hygiene facilities in Bangladesh: Insights from BDHS 2022 data

Mahmila Sanjana Mim; Md. Lutfor Rahaman; Anamul Haque Sajib

doi:10.1371/journal.pone.0318467

Peer Review History

Original SubmissionJanuary 17, 2025
Decision Letter - Md. Moyazzem Hossain, Editor Dear Dr. Mim, 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 May 16 2025 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. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Md. Moyazzem Hossain, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ****** Reviewer #1: Dear Authors, The article is very interesting in exploring determinants of WSH facilities ownership in Bangladesh using GLMM analysis. I understand the that article have important contribution in regards of the analytical methodology, however, the reader also expect thorough discussion in regards to the findings on the significant determinants. One of interesting findings is that respondents living in rural areas has higher chance to have basic sanitation facilities compare to urban areas. The author shows that similar finding from other studies, but it is worth to discuss to other studies that have contradicting findings. This could be provide detailed understanding on urban-rural discrepancy and reshape the recommendation for improving WASH service provision. Thank you Reviewer #2: echnical Soundness and Data Support: As stated in the introduction, the manuscript is complete from a technical point of view because it applied a Generalized Linear Mixed Model (GLMM) to account for intra cluster correlation in the BDHS 2022 data. The analysis of data demonstrated regionally WASH facilities in Bangladesh and the conclusions drawn were logic. Statistical Analysis: As mentioned previously, the statistical analysis is sophisticated, and for this task appropriate. GLMM was preferred to fixed-effect logistic regression as revealed by the AIC and LRT, ensuring correct inferences will be made with the clustered data. Data Availability: The data are available on the DHS website, therefore meeting fully accessible criteria for no restrictions of use. Language and Presentation: The text is very coherent and presented in standard English. Yet, small mistakes in typing and grammar should be amended in the revision. Additional Comments: The study is important in understanding WASH facilities in Bangladesh as the country strives to achieve the 6th SDG, and thus offers relevant contribution. Try to include more specific implications concerning the policies in the findings to increase the practical effect. Reviewer #3: The manuscript “Generalized Linear Mixed Model Approach for Analyzing Water, Sanitation, and Hygiene Facilities in Bangladesh: Insights from BDHS 2022 Data” presents a significant global health problem. While the topic is relevant, the manuscript requires significant revisions before it can be considered for publication. Major concerns: 1. While the machine learning model is a powerful algorithm, the manuscript lacks a clear justification for why the GLM method was chosen over other potential models. A more thorough comparison of different models and their suitability for this specific problem is needed. 2. The description of the data preprocessing, model selection, and evaluation methods needs to be significantly improved. There are vague statements and missing details. 3. This manuscript will benefit from spatial analysis with district-level data. 4. The manuscript does not adequately address the limitations of the study, such as potential biases in the data, the challenges of causal inference, and the generalizability of the findings. 5. The interpretation of the results sometimes appears overstated. The manuscript should be more cautious in drawing conclusions and acknowledge the uncertainties associated with the model predictions. 6. The figures and tables need to be improved in terms of clarity and presentation. 7. There are some inconsistencies in the referencing style. 8. The abstract is a bit too long and could be more concise. Specific Points: Methods: 1. Provide more details about the data sources, including specific databases and data collection procedures. 2. Clearly explain the data preprocessing steps, including how missing values were handled, how outliers were identified and treated, and how variables were standardized or normalized. Results: 1. Present the results of the model evaluation clearly and concisely. Include tables or figures showing the performance metrics for each model. 2. Provide more details about the key factors identified by the SHAP analysis (proposed). Discuss the potential mechanisms through which these factors influence Water, Sanitation, and Hygiene Facilities in Bangladesh. 3. Ensure that all tables and figures are properly labeled and referenced in the text. Discussion: 1. Discuss the limitations of the study in more detail. Acknowledge potential biases in the data, the challenges of causal inference, and the generalizability of the findings. 2. Compare the findings of this study with those of previous research. Discuss the similarities and differences and explain why the results might differ. 3. Provide more specific recommendations for public health interventions based on the findings of the study. Abstract: 1. Make the abstract more concise and focused. Highlight the key findings and their implications. ****** what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy Reviewer #1: Yes: Ni Made Utami Dwipayanti Reviewer #2: Yes: Hala Awad Ahmed Reviewer #3: Yes: Md. Siddikur Rahman ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0318467.r001
Revision 1
15 May 2025 Author Response PONE-D-25-02295 Generalized Linear Mixed Model Approach for Analyzing Water, Sanitation, and Hygiene Facilities in Bangladesh: Insights from BDHS 2022 Data I appreciate the feedback provided by the reviewers for our manuscript titled “Generalized Linear Mixed Model Approach for Analyzing Water, Sanitation, and Hygiene Facilities in Bangladesh: Insights from BDHS 2022 Data”. Answer to the Reviewers' comments: ________________________________________ 1. Is the manuscript technically sound, and do the data support the conclusions? 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: Yes Reviewer #3: No Answer: Thank you for acknowledging the technical soundness of our research. The primary contribution of our work lies in the investigation of key determinants of WASH facilities in Bangladesh by following GLMM approach. We have rigorously conducted the experiments, and the conclusions are drawn appropriately based on the data. However, the third reviewer disagreed. Considering the third reviewer’s comment, we have modified our “Conclusion” section so that it looks more appropriate.________________________________________ 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No Answers: We sincerely appreciate the first and second reviewer for recognizing the rigor and appropriateness of our statistical analysis. We also appreciate the disagreement of the third reviewer and his recommendation regarding the use of machine learning approach. However, our aim was to conduct the analysis under parametric framework. Performing machine learning analysis could be a future work. ________________________________________ 3. Have the authors made all data underlying the findings in their manuscript fully available? 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: Yes Reviewer #3: No Answer: Thank you so much. All data underlying the findings described in the manuscript are fully available on DHS website without any restriction. ________________________________________ 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No Answer: Thank you very much. We have carefully reviewed the manuscript and corrected grammatical errors. ________________________________________ 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Dear Authors, The article is very interesting in exploring determinants of WSH facilities ownership in Bangladesh using GLMM analysis. I understand that the article have important contribution in regards of the analytical methodology, however, the reader also expect thorough discussion in regards to the findings on the significant determinants. One of interesting findings is that respondents living in rural areas has higher chance to have basic sanitation facilities compare to urban areas. The author shows that similar finding from other studies, but it is worth to discuss to other studies that have contradicting findings. This could be provide detailed understanding on urban-rural discrepancy and reshape the recommendation for improving WASH service provision. Thank you. Answer: Thank you very much for your valuable comment. We have made thorough discussion in regards to the findings on the significant determinants according to your comment. Also, a discussion on the contradicting findings from other studies has been made in the “Discussion” section on page 30. Reviewer #2: Technical Soundness and Data Support: As stated in the introduction, the manuscript is complete from a technical point of view because it applied a Generalized Linear Mixed Model (GLMM) to account for intra cluster correlation in the BDHS 2022 data. The analysis of data demonstrated regionally WASH facilities in Bangladesh and the conclusions drawn were logic. Statistical Analysis: As mentioned previously, the statistical analysis is sophisticated, and for this task appropriate. GLMM was preferred to fixed-effect logistic regression as revealed by the AIC and LRT, ensuring correct inferences will be made with the clustered data. Data Availability: The data are available on the DHS website, therefore meeting fully accessible criteria for no restrictions of use. Language and Presentation: The text is very coherent and presented in standard English. Yet, small mistakes in typing and grammar should be amended in the revision. Answer: Thank you so much for such encouraging words. We have carefully revised the manuscript and corrected the typing mistakes and grammatical errors. Additional Comments: The study is important in understanding WASH facilities in Bangladesh as the country strives to achieve the 6th SDG, and thus offers relevant contribution. Try to include more specific implications concerning the policies in the findings to increase the practical effect. Answer: Thank you very much. We have included more specific implications according to your recommendation in the “Conclusion” section on page 31. Reviewer #3: The manuscript “Generalized Linear Mixed Model Approach for Analyzing Water, Sanitation, and Hygiene Facilities in Bangladesh: Insights from BDHS 2022 Data” presents a significant global health problem. While the topic is relevant, the manuscript requires significant revisions before it can be considered for publication. Major concerns: 1. While the machine learning model is a powerful algorithm, the manuscript lacks a clear justification for why the GLM method was chosen over other potential models. A more thorough comparison of different models and their suitability for this specific problem is needed. Answer: Thank you very much for your valuable comment. We really appreciate your recommendation. Our aim was to conduct the analysis under parametric (classical) framework. We wanted to take into account the cluster effect which exists in the dataset that we used. The reason behind the application of the mixed-effect logistic regression model (GLMM) has also been mentioned in the manuscript on page 4. Moreover, a comparison with fixed-effect logistic regression model (GLM) has been made and hence, the appropriateness of using the GLMM over the GLM has been justified. The comparison can be found in the manuscript on page 28. 2. The description of the data preprocessing, model selection, and evaluation methods needs to be significantly improved. There are vague statements and missing details. Answer: Thank you so much. We have improved the description of the data processing method in “Statistical Analyses” section on page 9. Also, the model selection, and evaluation methods have been improved in the “Mixed-Effect vs. Fixed Effect Logistic Regression Model” section on the pages 27 and 28. 3. This manuscript will benefit from spatial analysis with district-level data. Answer: Thank you very much for your thoughtful suggestion regarding the incorporation of spatial analysis using district-level data. We truly appreciate the insight, and I agree that this approach could provide valuable localized insights into geographic disparities in WASH facilities. However, given the current scope and focus of this study, we have chosen not to include spatial analysis at this time. We intend to explore this promising avenue in future research, as it would allow for a more detailed examination of district-level variations and further enhance policy recommendations. Thank you again for your valuable input. 4. The manuscript does not adequately address the limitations of the study, such as potential biases in the data, the challenges of causal inference, and the generalizability of the findings. Answer: Thank you so much. We have revised the manuscript and addressed the limitations adequately in the “Limitations and Further Scopes” section on page 32. 5. The interpretation of the results sometimes appears overstated. The manuscript should be more cautious in drawing conclusions and acknowledge the uncertainties associated with the model predictions. Answer: Thank you very much. We have modified the conclusion section based on your valuable suggestion. 6. The figures and tables need to be improved in terms of clarity and presentation. Answer: Thank you very much. As per your recommendation, we have improved the tables. 7. There are some inconsistencies in the referencing style. Answer: Thank you very much. Referencing styles have been standardized. APA referencing style has been adhered. 8. The abstract is a bit too long and could be more concise. Answer: Thank you so much. We have concised the abstract. Specific Points: Methods: 1. Provide more details about the data sources, including specific databases and data collection procedures. Answer: Thank you so much. More details about the data sources, including specific databases and data collection procedures have been provided in the “Data Sources” section on page 5 in the revised manuscript. 2. Clearly explain the data preprocessing steps, including how missing values were handled, how outliers were identified and treated, and how variables were standardized or normalized. Answer: Thank you very much. According to your valuable comment, a clear explanation regarding the data preprocessing steps has been provided on page 9 in the “Statistical Analyses” section. Results: 1. Present the results of the model evaluation clearly and concisely. Include tables or figures showing the performance metrics for each model. Answer: Thank you so much. We have presented the results of the model evaluation clearly and concisely in the revised manuscript. 2. Provide more details about the key factors identified by the SHAP analysis (proposed). Discuss the potential mechanisms through which these factors influence Water, Sanitation, and Hygiene Facilities in Bangladesh. Answer: Thank you very much. We have not considered SHAP analysis in our study. We may explore this in future research. But we have provided more details about the key factors identified by GLMM approach and discussed the potential mechanisms through which these factors influence WASH Facilities in Bangladesh. 3. Ensure that all tables and figures are properly labeled and referenced in the text. Answer: Thank you so much. In the revised manuscript, we have ensured that all tables and figures are properly labeled and referenced in the text. Discussion: 1. Discuss the limitations of the study in more detail. Acknowledge potential biases in the data, the challenges of causal inference, and the generalizability of the findings. Answer: Thank you very much. A detailed discussion has been made regarding the limitations of the study according to your recommendation. 2. Compare the findings of this study with those of previous research. Discuss the similarities and differences and explain why the results might differ. Answer: Thank you so much. According to your valuable comment, we have compared the findings of this study with those of previous research in the “Discussion” section on the pages 29 and 30 in the revised manuscript. 3. Provide more specific recommendations for public health interventions based on the findings of the study. Answer: Thank you very much. In the revised manuscript, we have provided more specific recommendations for public health interventions based on the findings of the study. Abstract: 1. Make the abstract more concise and focused. Highlight the key findings and their implications. Answer: Thank you so much. We have made the abstract more concise and focused in the revised manuscript. ________________________________________ 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Ni Made Utami Dwipayanti Reviewer #2: Yes: Hala Awad Ahmed Reviewer #3: Yes: Md. Siddikur Rahman Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0318467.r002
Decision Letter - Md. Moyazzem Hossain, Editor Generalized Linear Mixed Model Approach for Analyzing Water, Sanitation, and Hygiene Facilities in Bangladesh: Insights from BDHS 2022 Data PONE-D-25-02295R1 Dear Dr. Mim, 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. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Md. Moyazzem Hossain, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions??> Reviewer #1: Yes Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: Yes Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: Yes ****** Reviewer #1: Thank you for responding my comments and revise accordingly. To my understanding, the bivariate analysis actually showed a different result, that urban dweller is more likely to have access to handwashing facility and basic sanitation access. But yes, different methods of analysis might lead to different results Reviewer #2: The revised manuscript titled "Generalized Linear Mixed Model Approach for Analyzing Water, Sanitation, and Hygiene Facilities in Bangladesh: Insights from BDHS 2022 Data" demonstrates considerable improvement over the previous version. The authors have addressed the reviewers' concerns with care and thoroughness. The justification for choosing the Generalized Linear Mixed Model (GLMM) over other modeling approaches has been clearly explained and is appropriate given the clustered nature of the BDHS data. Statistical analysis is methodologically sound, appropriately applied, and well-supported by the data. The revisions to the manuscript’s structure, language, and clarity have made the content more intelligible and accessible. Typographical and grammatical errors noted previously have been corrected. The data availability statement complies with PLOS ONE’s policy, with the dataset being accessible on the DHS website. The authors have strengthened the discussion of their findings, acknowledged limitations, and expanded the policy implications to enhance practical relevance. While suggestions such as spatial analysis and SHAP were acknowledged as future work, the current scope remains valid and valuable for publication. I recommend accepting this manuscript for publication. ****** what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy Reviewer #1: Yes: Ni Made Utami Dwipayanti Reviewer #2: Yes: Hala Awad Ahmed ******** https://doi.org/10.1371/journal.pone.0318467.r003
Formally Accepted
Acceptance Letter - Md. Moyazzem Hossain, Editor PONE-D-25-02295R1 PLOS ONE Dear Dr. Sajib, 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. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Md. Moyazzem Hossain Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0318467.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .