Iron status and anemia in a representative sample of US pregnant women is not associated with pre-pregnancy BMI: Results from the NHANES (1999–2010) study

Mihaela A. Ciulei; Kelly Gallagher; Djibril M. Ba; Celeste Beck; Ruth A. Pobee; Alison D. Gernand; Rachel E. Walker

doi:10.1371/journal.pone.0300912

Peer Review History

Original SubmissionMarch 6, 2024
9 Apr 2024 Decision Letter - Marly A. Cardoso, Editor PONE-D-24-08813Iron status in a representative sample of US pregnant women is not associated with pre-pregnancy BMI: results from the NHANES (1999-2010) studyPLOS ONE Dear Dr. Walker, 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. In addition to reviewers´ comments, please describe the procedures for selection of covariables used in the multiple adjusted models. One important concern is the small number of observations for the outcomes (anemia and iron deficiency anemia): this point should be discussed in relation to the limitations of sample power and external validity. ============================== Please submit your revised manuscript by May 24 2024 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. Please include the following items when submitting your revised manuscript: 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, Marly A. Cardoso, Ph.D. 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. 2. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [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? 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: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 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 ****** 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 ****** 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: Thank you for the opportunity to read this interesting manuscript. I am pleased to see this paper that explores the association between pre-pregnancy BMI, iron status and anemia in a nationally representative sample of US pregnant women. In my opinion, the manuscript is a good piece of work, well structured, clear and easy to follow and understand. The introduction section is well presented, provides a contextualization of the topic addressed and presents the justification for the study. The methods section provides sufficient information, is well detailed and can be replicated. The statistical analyses are sound and the results are robust. The conclusions are well-stated and, in the discussion section, the authors explain the results and make relevant comparisons with previous studies. I have only 2 minor suggestions: 1. I suggest to include anemia in the title and objective of the study, since you also assessed this outcome in addition to iron status. 2. In the abstract (line 36), check the PR value for ID (overweight). It is different from what is shown in Table 2. Reviewer #2: Reviewer Report: This is an interesting study on Iron status among US pregnant women. I propose to address the following minor issues. Abstract: Abstract was written properly. Introduction: Introduction is written properly. Methods: Study population: How the sample size was calculated? Is this sample sufficient to produce enough power? Results: It is better to put one figure to show the principle finding to make it easily understandable by the general reader. Discussion: Inflammation is predicted to be responsible for anemia among obese/overweight individuals, and CRP is a marker of inflammation. The author reported prevalence of women with CRP>0.5 mg/L. It was better to show the prevalence of women with iron deficiency based on the category of CRP. ****** 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: No Reviewer #2: Yes: Md Kamruzzaman ******** [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.0300912.r001
Revision 1
10 May 2024 Author Response In addition to reviewers´ comments, please describe the procedures for selection of covariables used in the multiple adjusted models. Author comments: We selected covariables a priori based on prior literature of factors known to be related to iron and anemia status and BMI during pregnancy (please see the Methods/Covariates section, lines 136-140). One important concern is the small number of observations for the outcomes (anemia and iron deficiency anemia): this point should be discussed in relation to the limitations of sample power and external validity. Author comments: Thank you for pointing out the small number of observations for the anemia and iron deficiency anemia outcomes. We followed the CDC guidelines and flagged the estimates that had a small sample size (<30). We thought the readers should see these results but interpret them with caution given the small sample size. We pointed this limitation out in the table footnotes, Results section (lines #237-240) and Strengths & Limitations section (lines #357-360). Reviewer #2 also had questions regarding our sample size and power, please see our answer under Methods (first question). Comments to the Author Reviewer #1: Thank you for the opportunity to read this interesting manuscript. I am pleased to see this paper that explores the association between pre-pregnancy BMI, iron status and anemia in a nationally representative sample of US pregnant women. In my opinion, the manuscript is a good piece of work, well structured, clear and easy to follow and understand. The introduction section is well presented, provides a contextualization of the topic addressed and presents the justification for the study. The methods section provides sufficient information, is well detailed and can be replicated. The statistical analyses are sound and the results are robust. The conclusions are well-stated and, in the discussion section, the authors explain the results and make relevant comparisons with previous studies. I have only 2 minor suggestions: 1. I suggest to include anemia in the title and objective of the study, since you also assessed this outcome in addition to iron status. Author comments: Thank you for this helpful suggestion, which will provide more clarity to our readers regarding what we examined. We incorporated the term anemia in our title (lines 1-2), objective (line 75), and throughout the manuscript. 2. In the abstract (line 36), check the PR value for ID (overweight). It is different from what is shown in Table 2. Author comments: Thanks for spotting this discrepancy; it is now fixed. Line 37: “There were no differences in the prevalence of ID or anemia in women with pre-pregnancy overweight and obesity (ID: overweight, adjusted prevalence ratio (PR)=1.27, 95%CI: 0.89-1.82; obesity, PR=0.75, 95%CI: 0.39-1.45.” In addition, we found that the p-values reported in the Figure 1 legend did not match the figure because they were from a previous version of the statistical analysis. We have updated the legend to be the correct numbers (lines 228-229). Reviewer #2: Reviewer Report: This is an interesting study on Iron status among US pregnant women. I propose to address the following minor issues. Abstract: Abstract was written properly. Introduction: Introduction is written properly. Methods: Study population: How the sample size was calculated? Is this sample sufficient to produce enough power? Author comments: Thanks for this question. As described in lines 81-91, our sample size was based on years of available NHANES data in which iron status biomarkers were measured. Importantly, our sample size of 1,156 was larger than other US studies that have investigated the association between BMI and iron status (Cao et al., 2016 and Dao et al., 2013). It is quite difficult to find studies of pregnant women with a larger sample size, especially a nationally representative sample. Using the Poisson regression option in Gpower to conduct a post hoc power analysis, a sample size of 1,156 would give us >80% power to detect significant iron deficiency prevalence ratios of 1.5-2.0 (50-100% difference). However, we did not have enough power to detect the small observed differences between groups, especially with the low number of observed cases of anemia and IDA. We have added a description of the power calculation in the Methods (lines 91-96), Results (lines 240-251), and Strengths and Limitations (lines 360-363). In our reporting, we followed the CDC guidelines (reference 47), which indicate that the effective number of cases should not be smaller than 30. We flagged such findings in our results. For instance, in Table 2, we indicate in the footnote that estimates from anemia and iron deficiency anemia in association with BMI categories may be unreliable due to a total number of cases less than 30. Results: It is better to put one figure to show the principle finding to make it easily understandable by the general reader. Author comments: Thank you for this comment – we agree that figures are important and help the reader easily understand the findings. In this case, we present the continuous biomarker results, the first part of our main findings, in a figure. However, we felt that the details of our main prevalence model results were best displayed in a table. While we could add another figure to the paper, we were following the general guidelines of not replicating the same results across tables and figures. Discussion: Inflammation is predicted to be responsible for anemia among obese/overweight individuals, and CRP is a marker of inflammation. The author reported prevalence of women with CRP>0.5 mg/L. It was better to show the prevalence of women with iron deficiency based on the category of CRP. Author comments: We welcome this valuable suggestion. We tested to see if inflammation (CRP>5 mg/L) was associated with cases of iron deficiency or IDA. We observed no differences by inflammatory status. This has been added to Table 1. Additionally, a prior publication by Mei et al., (reference #9) tested if inflammation impacts the prevalence of iron deficiency and anemia in pregnant women (used the same cycles as us but included a slightly different age range). Specifically, Mei et al., tested the results in the total sample and a subsample (removed pregnant women with CRP>5 mg/L) and found that the prevalence of ID in the subsample was not substantially different from the one from the total sample (reference #9). As such, our results are consistent with this prior publication. Attachments Attachment Submitted filename: Response to reviewers_May.9.2024.docx* https://doi.org/10.1371/journal.pone.0300912.r002
14 May 2024 Decision Letter - Marly A. Cardoso, Editor PONE-D-24-08813R1Iron status and anemia in a representative sample of US pregnant women is not associated with pre-pregnancy BMI: results from the NHANES (1999-2010) studyPLOS ONE Dear Dr. Walker, 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. The authors have made a good revision of the manuscript. However, an improvement on the description of the selection of covariates for multiple adjustment models is still necessary. Please submit your revised manuscript by Jun 28 2024 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. Please include the following items when submitting your revised manuscript: 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, Marly A. Cardoso, Ph.D. Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Additional Editor Comments: The authors have made a good revision of the manuscript. However, I suggest reviewing and providing details on how the covariates were selected for multiple models to avoid residual confounding. The authors have replied that "We selected covariables a priori based on prior literature of factors known to be related to iron and anemia status and BMI during pregnancy (please see the Methods/Covariates section, lines 136-140)." - saying just "based on prior literature" is not enough! There are many ways to test multiple adjustment models. I recommend the use of a hierarchical conceptual framework combined with different p-values for each determinant level. Please see the following recent paper: NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet. 2024 Mar 16;403(10431):1027-1050. doi: 10.1016/S0140-6736(23)02750-2. [Note: HTML markup is below. Please do not edit.] [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.0300912.r003
Revision 2
4 Jun 2024 Author Response Thank you to the editor for thoughtful consideration of our manuscript. Below are our responses to the comments from the editor in response to our last revision. Author responses are below editor comments. All line numbers refer to the clean manuscript version. Additional Editor Comments: The authors have made a good revision of the manuscript. However, I suggest reviewing and providing details on how the covariates were selected for multiple models to avoid residual confounding. The authors have replied that "We selected covariables a priori based on prior literature of factors known to be related to iron and anemia status and BMI during pregnancy (please see the Methods/Covariates section, lines 136-140)." - saying just "based on prior literature" is not enough! There are many ways to test multiple adjustment models. I recommend the use of a hierarchical conceptual framework combined with different p-values for each determinant level. Please see the following recent paper: NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet. 2024 Mar 16;403(10431):1027-1050. doi: 10.1016/S0140-6736(23)02750-2. Author comments: Thank you for your comments and explanation. We have carefully reviewed the request and would like to note that there are significant differences between our methods and the paper that the editor kindly shared (doi: 10.1016/S0140-6736(23)02750-2). In the shared paper, researchers conducted a multi-level, longitudinal analysis using Bayesian models. Our analysis used a cross-sectional design (not hierarchical or multi-level) of a large dataset using complex survey design to obtain a nationally representative sample in the US (DHHS publication; nos. (PHS) 2013–1360 & (PHS) 2012–1355; https://wwwn.cdc.gov/nchs/nhanes/analyticguidelines.aspx#sample-design). The weighting procedures required for complex survey designs make it difficult to assess true correlation and collinearity between covariates within a model. We reviewed current practices for covariate identification and adjustment and see others in the field apply a similar approach to ours. Recent articles in PLOS One have used similar approaches to ours when conducting a similar analysis (e.g. doi: 10.1371/journal.pone.0303169). Additionally, other analyses of iron status with the NHANES data used the same or similar covariates (see: doi: 10.3945/ajcn.110.007195, 10.1371/journal.pone.0112216, and 0.3945/ajcn.117.155978). Therefore, we feel that our analysis is most comparable to these previously published reports when we include a similar list of covariates. For these reasons, we consider that our method of covariate selection was the appropriate approach in this case. We acknowledge that using hierarchical Bayesian criteria may be preferred when a dataset has a hierarchical or multi-level structure. We have updated our Methods section to better describe our approach and reference comparable literature in lines 136-139. Attachments Attachment Submitted filename: Response to reviewers_May.29.2024.docx https://doi.org/10.1371/journal.pone.0300912.r004
5 Jun 2024 Decision Letter - Marly A. Cardoso, Editor PONE-D-24-08813R2Iron status and anemia in a representative sample of US pregnant women is not associated with pre-pregnancy BMI: results from the NHANES (1999-2010) studyPLOS ONE Dear Dr. Walker, 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. The revision of the procedures for data analysis needs improvement as recommended. Please submit your revised manuscript by Jul 20 2024 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. Please include the following items when submitting your revised manuscript: 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, Marly A. Cardoso, Ph.D. Academic Editor PLOS ONE Additional Editor Comments: The authors did not review the procedures for the selection of covariables in multiple regression models as recommended. In my previous comments, I have suggested a recent paper as an example of the use of hierarchical conceptual framework for selection of independent variables, independent of using Bayesian approach or any other statistical regression models. In the revised manuscript, the description of "we would expect to be associated with iron status based on prior literature" is not enough. There are so many methodological articles on this point and the authors must consider this revision. There is a classical paper on this (Victora CG, Huttly SR, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol. 1997 Feb;26(1):224-7. doi: 10.1093/ije/26.1.224) among many others combining conceptual frameworks with p-value and changes in the oucome measure estimates for selection of independent variables. [Note: HTML markup is below. Please do not edit.] [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.0300912.r005
Revision 3
16 Jul 2024 Author Response Additional Editor Comments: The authors did not review the procedures for the selection of covariables in multiple regression models as recommended. In my previous comments, I have suggested a recent paper as an example of the use of hierarchical conceptual framework for selection of independent variables, independent of using Bayesian approach or any other statistical regression models. In the revised manuscript, the description of "we would expect to be associated with iron status based on prior literature" is not enough. There are so many methodological articles on this point and the authors must consider this revision. There is a classical paper on this (Victora CG, Huttly SR, Fuchs SC, Olinto MT. The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. Int J Epidemiol. 1997 Feb;26(1):224-7. doi: 10.1093/ije/26.1.224) among many others combining conceptual frameworks with p-value and changes in the oucome measure estimates for selection of independent variables. Author comments: Thank you for the opportunity to improve and resubmit this study. We have taken your recommendation to utilize a hierarchical conceptual framework for covariate selection. We have considered the methodology described by Victora et al., and have incorporated it into our statistical methods (see attached conceptual framework diagram). We describe this process in the Methods section (lines 182-199). Based on this process, we decided to remove family income from the adjusted models in this work, since it would likely be on the causal pathway between education and iron status outcomes and was not associated with iron outcomes in unadjusted models. Results, including tables and figures, have been revised accordingly. We hope you agree that this improves the interpretation of the results. Please let us know if you have any remaining questions about these adjusted models. https://doi.org/10.1371/journal.pone.0300912.r006
24 Jul 2024 Decision Letter - Marly A. Cardoso, Editor Iron status and anemia in a representative sample of US pregnant women is not associated with pre-pregnancy BMI: results from the NHANES (1999-2010) study PONE-D-24-08813R3 Dear Dr. Walker, 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, Marly A. Cardoso, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0300912.r007
Formally Accepted
30 Jul 2024 Acceptance Letter - Marly A. Cardoso, Editor PONE-D-24-08813R3 PLOS ONE Dear Dr. Walker, 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 If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks 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 Dr. Marly A. Cardoso Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0300912.r008

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