Review for 10.1186/s12876-025-04006-7 (2025)

Title: Relative Fat Mass and Risk of Metabolic Dysfunction Associated Steatotic Liver Disease
and Severe Hepatic Steatosis in U.S. Adults: Analysis of NHANES 2017–2020 Data
Version: 1 Date: 25 Apr 2025
Reviewer:  Amira A. A. Othman
Reviewer's report:
First of all
I want to congratulate the authors on their work. In this study, Wang et al. in this manuscript
aimed to explore a timely and clinically relevant topic—examining the relationship between
Relative Fat Mass (RFM) and the prevalence of nonalcoholic fatty liver disease (NAFLD) and
severe hepatic steatosis (SHS) in the U.S. adult population using NHANES data. The authors
have undertaken a robust statistical analysis to support the hypothesis that RFM, a relatively
novel metric, may be a more accurate and practical predictor of liver steatosis compared to
traditional anthropometric indicators like BMI. The study is thorough, well-structured, and
largely methodologically sound, offering valuable insights that may help improve early detection
and prevention strategies for NAFLD/SHS. That said, several areas require attention to improve
clarity, scientific rigor, and manuscript quality..
Non-alcoholic fatty liver disease (NAFLD) is recognized as the most prevalent chronic liver
disease, impacting about 30% of global individuals, with the potential to progress to advanced
hepatic fibrosis and end-stage liver diseases eventually [*]. In June 2023, a multi-society
committee of international experts was gathered, and new terminology was adopted to reduce
stigma and increase disease awareness [**]. A new terminology, Steatotic liver disease (SLD),
replaces “fatty liver disease” as the umbrella term. Under subgroups of SLD, NAFLD has been
renamed as metabolic dysfunction-associated Steatotic liver disease (MASLD) [**]. NAFLD/
MASLD is closely related to metabolic syndrome (MetS) and its associated components of
hypertension, type 2 diabetes mellitus, dyslipidemia, and obesity[***].
(*:doi: 10.1097/HEP.0000000000000004, **: doi: 10.1016/j.jhep.2023.06.003, ***  doi:
10.1111/apt.17308).
The authors handled the reviewer comments satisfactorily, nevertheless, there is an observation
for which sufficient justification must be obtained.
In general:
1. The language is generally clear, but some minor grammatical errors and awkward phrasings
could be improved. Consider having the manuscript proofread by a native English speaker or
a professional editing service.
2. Abbreviations must be fully written at their first appearance.
In Title:
1. The title should indicate the age and locality of the study population at which the National
Health and Nutrition Examination Survey (NHANES) was performed. I suggest “ Relative
Fat Mass and Risk of Nonalcoholic Fatty Liver Disease and Severe Steatosis in U.S. Adults:
Analysis of NHANES 2017–2020 Data”.
In the Abstract section
2. The background subsection in the abstract :
-  Should be the shortest part of the abstract. It should briefly outline the following information:
What is already known about the subject, related to the paper in question. What is not known
about the subject, and hence what the study intended to examine (or what the paper seeks to
present)? Please reconstruct it properly.
- Define “SHS” at first mention.
3. In the method subsection in the abstract :
- It would help if you described the aim of your statistical analysis.
- Consider summarizing methods more concisely and focusing more on key results and
implications.
- The type of study: a population-based study.
In the results subsection in the abstract :
-   good
4. In the conclusion subsection in the abstract :
- Rephrase the conclusion to emphasize the clinical relevance of using RFM in population
screening.
In the Introduction section:
5. Try to provide a summarized description of the National Health and Nutrition Examination
Survey (NHANES) in the background section. You may use the following: “NHANES
(www.cdc.gov/nchs/nhanes) is designed to assess the health and nutritional status of adults
and children in the United States. The survey is distinctive in that it incorporates both
physical examinations and interviews. Several cross-sectional, nationally representative health
examination surveys are part of the NHANES program. Questions about demographics,
health insurance status, dietary habits, acute and chronic medical issues, mental health, and
prescription drug use are all included in the health interview. Exam components can change
between survey cycles but typically include blood pressure, dental exams, vision, hearing,
dermatology, fitness, balance and strength testing, respiratory testing, taste and smell, and
body measurements (weight, height, skin folds, body composition scans). Hematology, organ
and endocrine function (e.g., thyroid, kidney), environmental exposure, dietary biomarkers,
metabolic and cardiovascular health, and infectious disease are a few examples of laboratory
components.
6. MAFLD must replace NAFLD:
“In contrast to NAFLD, MAFLD does not necessitate ruling out other liver disease causes, such
as viral hepatitis or heavy alcohol use*. The new name chosen to replace NAFLD reflected the
disease etiology better and conveyed a more practical approach in daily clinical practice than
NAFLD, considering its close association with metabolic syndrome**. Please discuss the new
nomenclature in more detail.
(*: Doi: 10.1016/j.jhep.2020.03.039, **: doi: 10.1097/HEP.0000000000000520)
7. Trim redundant discussions on obesity mechanisms already well-established.
8. Move the discussion of RFM’s advantages earlier to foreground its importance.
9. Clarify the knowledge gap and highlight the novelty, e.g., “This is among the first population-
based studies exploring nonlinear associations and threshold effects of RFM on SHS.”
In the Methods section:
10. Please move the sentences defining the NHANES to the introduction section rather than the
methodology section.
11. The study utilized the 2017-2020 NHANES survey cycle. why did you choose the study
survey cycle? The survey includes study cycles from 2001 to 2023.
12. Please provide the participants' sociodemographic data.
13. How the sample size was calculated.
14. Mention ethical approval earlier in the methodology to emphasize compliance.
15. Separate participant inclusion/exclusion criteria with bullet points or a structured table for
readability.
16. Specify the rationale for selected covariates in the regression models (particularly in Model
3).
17. Include software and package names for reproducibility (e.g., R packages used for curve
fitting).
In the Results section:
18. In all tables, please explain the abbreviations under the tables.
19. You can title the statistical test column as “Test of significance” and use U= for the Mann–
Whitney U test, T= for the T-test, and #2 = for the Chi-square test, etc.. Although the Chi-square
test was used to compare observed and expected results, nothing was mentioned in the statistical
analysis section.
20. Avoid overly technical sentences, e.g., clarify “threshold effect” in lay language where
appropriate.
21. Summarize key data trends from large tables and figures directly in the text to aid
understanding.
22. Ensure consistency of terminology: sometimes "RFM quartile" and sometimes "RFM level"
are used interchangeably.
23. Use uniform decimal precision across all tables.
In the Discussion section:
24. The discussion section is one of the final parts of a research paper, in which an author
describes, analyzes, and interprets their findings. They explain the significance of those results
and tie everything back to the research question(s). In this manuscript, there is confusion
between what should be written in the introduction and discussion sections. Please reconstruct
the discussion section.
25. Reorganize for flow: start with summary of findings, then mechanisms, then implications.
26. Discuss potential limitations of RFM (e.g., may not reflect visceral fat distribution).
27. Expand slightly on how findings may translate into public health strategies or clinical
guidelines.
In the Conclusion section:
28. Rephrase to emphasize the clinical utility: e.g., “RFM may serve as a valuable, non-invasive
screening tool forMAFLD and SHS risk in diverse adult populations.”