PONE-D-24-15594Methodology for developing and validating Bangladesh Healthy Eating Index: A Study protocolPLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

The research question outlined is expected to address a valid academic problem or topic and contribute to the base of knowledge in the field.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses?

The manuscript should describe the methods in sufficient detail to prevent undisclosed flexibility in the experimental procedure or analysis pipeline, including sufficient outcome-neutral conditions (e.g. necessary controls, absence of floor or ceiling effects) to test the proposed hypotheses and a statistical power analysis where applicable. As there may be aspects of the methodology and analysis which can only be refined once the work is undertaken, authors should outline potential assumptions and explicitly describe what aspects of the proposed analyses, if any, are exploratory.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable?

Descriptions of methods and materials in the protocol should be reported in sufficient detail for another researcher to reproduce all experiments and analyses. The protocol should describe the appropriate controls, sample size calculations, and replication needed to ensure that the data are robust and reproducible.

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors described where all data underlying the findings will be made available when the study is complete?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception, at the time of publication. 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: No

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5. 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

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

(Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is an interesting study on “Methodology for developing and validating Bangladesh Healthy Eating Index: A Study protocol”.

My comments are appended.

Abstract:

Abstract has been written in right direction.

Introduction:

Introduction has been written in right direction.

Methods:

Line 93: Weighing, standard, and scoring: The author needs to put some arguments, why all eight groups of foods are given equal weight?

Line 138: How the sample size was calculated needs to be mentioned. Is this sample size 1080 representative to whole Bangladesh? Ensuring proper sample size, the author need to ensure external validity of the study.

Line 143: The mentioned correlation between dietary pattern and food security with cropping pattern and agricultural productivity may not be true in all areas like in urban settings. Moreover, due to socioeconomic, demographic and nutrition transition, availability of processed foods has become easily accessibly in rural areas, while rural area is higher productive in terms of agriculture. Moreover, people from agriculturally productive areas may sell their produce, rather than consuming, to afford other household commodities. For instance, farmer producing vegetables does not necessarily ensure that they will consume more vegetables. The author may reconsider their sampling procedure to make their study more representative to whole Bangladesh.

Line 176: The author mentioned that two consecutive days 24h dietary data of will be collected. 24H data provide short term dietary intake pattern. For long term dietary intake pattern, it is better to include FFQ and to compare 24H data with FFQ.

Reviewer #2: Summary

In this study, authors describe the methodological approach to the development and validation of a healthy eating index specific for Bangladeshi population. The index is based on the food-based dietary guidelines of Bangladesh and includes 8 components. For evaluation, diet will be assessed using repeated 24-h dietary recalls among 1080 reproductive age women. Developing an index tailored to dietary recommendations is relevant and the analysis plan for evaluation is well described. However, the usual intake estimation approach may not be adequate for the intended analysis (see first major comment). Also, I think it would be relevant to better describe how the score may be revised or adapted given the evaluation results (see second major comment).

Major

Usual intake estimation (L185). To my knowledge, the MSM procedure does not support bivariate analysis (e.g., joint measurement error correction of a score for a component and nutrient intake) or multivariate analysis (joint measurement error correction for the 8 components of the score to calculate the total score and nutrient intake). If it is the case, this is a major limitation of the planned usual intake analysis. Bias is expected. A state-of-the-art analysis would also use methods such as the National Cancer Institute multivariate Markov Chain Monte Carlo (MCMC) algorithm (Zhang, Krebs-Smith, et al., 2011; Zhang, Midthune, et al., 2011). The MCMC method would allow authors to generate measurement-error corrected data suitable to estimate usual intake distribution, multidimensionality and internal consistency analysis. This would not be possible with the MSM method.

In table 2, authors state their hypothesis (“Expectation”) regarding the evaluation. I think it would be useful to expand on 1) the rationale for these hypotheses; 2) the possibility that the hypotheses are *not* verified. For example, what if the score does not show many variations for a given component? How would authors approach or revise their scoring? What if the score is highly dependent on energy intake (see specific minor comments below)? What if some components of the score are inversely associated and show poor internal consistency? All in all, pre-specifying how the components or the scoring may be modified given the evaluation results will allow authors to have more flexibility once the evaluation results are known. Otherwise, there is a risk that authors find poor evaluation metrics and are stuck with a score that is not useful.

Minor

Scoring for the optimum component. This scoring approach sometimes results in poor internal consistency and may not “work” well within a score. Authors should examine or consider alternative scoring approach if the optimum components show poor results during the evaluation analysis. To be clear, I am not saying that authors should not use the “optimum scoring approach”, but rather consider that the approach may not work well within a total score. Expanding the discussion or method section regarding this possibility may be relevant.

Data analysis plan. The sampling strategy may require the use of survey-specific procedures or statistical analyses instead of standard procedures. I recommend authors mention how the sampling design will be considered, e.g., stratification, clustering, weighting accounted for using bootstrap or BRR variance estimation and sampling weights.

For construct validity, it would be relevant to add the (expected) relationship between sociodemographic characteristics and scores. For example, older adults typically have greater diet quality than younger adults and non-smoker typically have greater diet quality than smokers, at least in a North American context (Reedy et al., 2018). Authors could also select other characteristics that are more relevant to their context.

Authors expect a weak correlation between energy intake and the score (L216, table 2). However, many components are scored in the absolute scale (e.g., fruits >= 1 serving/day or sugar <= 5 servings/day). Typically, scoring on the absolute scale *is* associated with energy intake, because the amount of food eaten influence the probability of eating more or less than (absolute) thresholds. While the evaluation may show that this is not a major issue for the score per se, I think authors should further describe why they expect a weak correlation or revise their hypothesis. Also, the use of an absolute approach vs. a relative scoring approach (e.g., % of total energy as in the US-HEI) should be discussed.

References

Reedy, J., Lerman, J. L., Krebs-Smith, S. M., Kirkpatrick, S. I., Pannucci, T. E., Wilson, M. M., Subar, A. F., Kahle, L. L., & Tooze, J. A. (2018). Evaluation of the Healthy Eating Index-2015. J Acad Nutr Diet, 118(9), 1622-1633. https://doi.org/10.1016/j.jand.2018.05.019

Zhang, S., Krebs-Smith, S. M., Midthune, D., Perez, A., Buckman, D. W., Kipnis, V., Freedman, L. S., Dodd, K. W., & Carroll, R. J. (2011). Fitting a bivariate measurement error model for episodically consumed dietary components. Int J Biostat, 7(1), 1. https://doi.org/10.2202/1557-4679.1267

Zhang, S., Midthune, D., Guenther, P. M., Krebs-Smith, S. M., Kipnis, V., Dodd, K. W., Buckman, D. W., Tooze, J. A., Freedman, L., & Carroll, R. J. (2011). A New Multivariate Measurement Error Model with Zero-Inflated Dietary Data, and Its Application to Dietary Assessment. Ann Appl Stat, 5(2B), 1456-1487. https://doi.org/10.1214/10-AOAS446

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Reviewer #1: Yes: Md Kamruzzaman

Reviewer #2: No

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Methodology for developing and validating Bangladesh Healthy Eating Index: A Study protocol

PONE-D-24-15594R1

Dear Dr. Islam,

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.

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Kind regards,

Muttaquina Hossain, MBBS, MPH

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

The research question outlined is expected to address a valid academic problem or topic and contribute to the base of knowledge in the field.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses?

The manuscript should describe the methods in sufficient detail to prevent undisclosed flexibility in the experimental procedure or analysis pipeline, including sufficient outcome-neutral conditions (e.g. necessary controls, absence of floor or ceiling effects) to test the proposed hypotheses and a statistical power analysis where applicable. As there may be aspects of the methodology and analysis which can only be refined once the work is undertaken, authors should outline potential assumptions and explicitly describe what aspects of the proposed analyses, if any, are exploratory.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable?

Descriptions of methods and materials in the protocol should be reported in sufficient detail for another researcher to reproduce all experiments and analyses. The protocol should describe the appropriate controls, sample size calculations, and replication needed to ensure that the data are robust and reproducible.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors described where all data underlying the findings will be made available when the study is complete?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception, at the time of publication. 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

**********

5. 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

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

(Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thanks for your feedback and properly address issues raised by the reviewers. I hope the manuscript is now suitable for publication.

Reviewer #2: I thank the authors for diligently addressing my previous comments. Thank you for this work. I have no additional feedback to provide.

Please note that in addition to the currently available SAS version of the NCI MCMC algorithm ( https://prevention.cancer.gov/research-groups/biometry/measurement-error-impact/software-measurement-error/several-regularly-consumed-or-episodically-consumed-foods-or-nutrients-multivariate-distribution ), an R version of the MCMC algorithm should be made available by the NCI before completion of the study. Authors may be interested in this version, since it will be based on the open-source R software.

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7. 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: Md Kamruzzaman

Reviewer #2: No

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