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: 03 May 2025
Reviewer's report:
This cross-sectional study utilizes NHANES data (2017–2020) to evaluate the association
between relative fat mass (RFM) and the prevalence of nonalcoholic fatty liver disease (NAFLD)
and severe hepatic steatosis (SHS). The authors report a positive, nonlinear association with
identifiable thresholds for RFM linked to increased disease prevalence. The study is based on a
large, nationally representative cohort, with robust statistical modeling and appropriate subgroup
analyses. It addresses a relevant clinical question using a novel adiposity index.
Major Concerns
• Causal inference limitation not sufficiently emphasized
While the cross-sectional nature is acknowledged, the manuscript language occasionally implies
causality (e.g., “RFM levels were positively associated with risk”). Stronger caution is warranted
in both the abstract and discussion to avoid misinterpretation.
• Inadequate handling of selection bias
The use of VCTE, which was performed voluntarily, could introduce selection bias. The authors
should provide more detail on how this may affect generalizability.
• Clinical implications remain vague
Despite identifying RFM thresholds, the practical utility of this information is unclear. How
these thresholds compare with current clinical cutoffs (e.g., BMI) or whether they improve
predictive capacity should be better discussed.
• Lack of external validation
The study could benefit from validation in a separate cohort, especially for the derived threshold
values of RFM. At minimum, the authors should mention this limitation explicitly and suggest
it as a future direction.
• Overadjustment in regression modeling
The fully adjusted Model 3 includes variables that may lie on the causal pathway (e.g., HbA1c,
CRP, ferritin). This could lead to overadjustment bias. Authors should discuss this limitation.
• Figures need improved labeling and clarity
Figures 1–3 (flowchart, curve fitting, and subgroup analysis) are hard to interpret without clearer
legends. For instance, Figure 2 lacks axis definitions and does not clearly explain what is meant
by the shaded area representing 95% CI.
Minor Concerns
• Terminology inconsistencies
The manuscript inconsistently uses “prevalence of NAFLD” and “risk of NAFLD.” Since this
is a prevalence-based study, all such statements should consistently use “prevalence” or “odds.”
• Statistical presentation
Some results in Table 3 and Table 4 are duplicated in the text with excessive decimal precision
(e.g., OR: 1.22, 95% CI: 1.18–1.26). It would be preferable to round to two significant digits
for readability.
• Missing information on missing data handling
It is unclear whether any imputation was used for missing covariates. The method of handling
missing data should be stated clearly.
• Redundancy in background section
The manuscript repeats general information about NAFLD multiple times in both the
Introduction and Discussion. The background could be shortened for better focus.
• Units missing in some variables
In Table 1, variables like CRP, ALT, and Alb lack units. These should be added for clarity #.
Limitations
• Potential misclassification of NAFLD/SHS due to VCTE thresholds
CAP thresholds are used instead of biopsy, which could lead to misclassification bias. Although
this is mentioned briefly, a deeper discussion is warranted.
• Lack of information on diet quality or physical activity
While sugar and energy intake are included, broader dietary patterns and lifestyle variables are
not considered, which could confound the association between RFM and liver disease.
• Sex-specific thresholds not explored
Although sex is adjusted for in RFM and subgroup analyses are conducted, the threshold analysis
did not report sex-specific thresholds. Given known sex differences in fat distribution, this is
a missed opportunity.
Language and Presentation
• The manuscript is well written overall, but some language revisions are necessary:
• Replace ambiguous terms like “risk” with “odds” or “association” when referring to cross-
sectional results.
• Avoid passive phrasing such as “NAFLD is diagnosed when…” and instead specify “In this
study, NAFLD was defined as…”
• Reword examples:
• “This study had several advantages.” # “This study presents several strengths.”
• “Therefore, our results accurately represent…” # “Thus, these findings reflect the prevalence
in the general adult U.S. population.”
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: 03 May 2025
Reviewer's report:
This cross-sectional study utilizes NHANES data (2017–2020) to evaluate the association
between relative fat mass (RFM) and the prevalence of nonalcoholic fatty liver disease (NAFLD)
and severe hepatic steatosis (SHS). The authors report a positive, nonlinear association with
identifiable thresholds for RFM linked to increased disease prevalence. The study is based on a
large, nationally representative cohort, with robust statistical modeling and appropriate subgroup
analyses. It addresses a relevant clinical question using a novel adiposity index.
Major Concerns
• Causal inference limitation not sufficiently emphasized
While the cross-sectional nature is acknowledged, the manuscript language occasionally implies
causality (e.g., “RFM levels were positively associated with risk”). Stronger caution is warranted
in both the abstract and discussion to avoid misinterpretation.
• Inadequate handling of selection bias
The use of VCTE, which was performed voluntarily, could introduce selection bias. The authors
should provide more detail on how this may affect generalizability.
• Clinical implications remain vague
Despite identifying RFM thresholds, the practical utility of this information is unclear. How
these thresholds compare with current clinical cutoffs (e.g., BMI) or whether they improve
predictive capacity should be better discussed.
• Lack of external validation
The study could benefit from validation in a separate cohort, especially for the derived threshold
values of RFM. At minimum, the authors should mention this limitation explicitly and suggest
it as a future direction.
• Overadjustment in regression modeling
The fully adjusted Model 3 includes variables that may lie on the causal pathway (e.g., HbA1c,
CRP, ferritin). This could lead to overadjustment bias. Authors should discuss this limitation.
• Figures need improved labeling and clarity
Figures 1–3 (flowchart, curve fitting, and subgroup analysis) are hard to interpret without clearer
legends. For instance, Figure 2 lacks axis definitions and does not clearly explain what is meant
by the shaded area representing 95% CI.
Minor Concerns
• Terminology inconsistencies
The manuscript inconsistently uses “prevalence of NAFLD” and “risk of NAFLD.” Since this
is a prevalence-based study, all such statements should consistently use “prevalence” or “odds.”
• Statistical presentation
Some results in Table 3 and Table 4 are duplicated in the text with excessive decimal precision
(e.g., OR: 1.22, 95% CI: 1.18–1.26). It would be preferable to round to two significant digits
for readability.
• Missing information on missing data handling
It is unclear whether any imputation was used for missing covariates. The method of handling
missing data should be stated clearly.
• Redundancy in background section
The manuscript repeats general information about NAFLD multiple times in both the
Introduction and Discussion. The background could be shortened for better focus.
• Units missing in some variables
In Table 1, variables like CRP, ALT, and Alb lack units. These should be added for clarity #.
Limitations
• Potential misclassification of NAFLD/SHS due to VCTE thresholds
CAP thresholds are used instead of biopsy, which could lead to misclassification bias. Although
this is mentioned briefly, a deeper discussion is warranted.
• Lack of information on diet quality or physical activity
While sugar and energy intake are included, broader dietary patterns and lifestyle variables are
not considered, which could confound the association between RFM and liver disease.
• Sex-specific thresholds not explored
Although sex is adjusted for in RFM and subgroup analyses are conducted, the threshold analysis
did not report sex-specific thresholds. Given known sex differences in fat distribution, this is
a missed opportunity.
Language and Presentation
• The manuscript is well written overall, but some language revisions are necessary:
• Replace ambiguous terms like “risk” with “odds” or “association” when referring to cross-
sectional results.
• Avoid passive phrasing such as “NAFLD is diagnosed when…” and instead specify “In this
study, NAFLD was defined as…”
• Reword examples:
• “This study had several advantages.” # “This study presents several strengths.”
• “Therefore, our results accurately represent…” # “Thus, these findings reflect the prevalence
in the general adult U.S. population.”
Please review this paper.
user
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: 03 May 2025
Reviewer's report:
This cross-sectional study utilizes NHANES data (2017–2020) to evaluate the association
between relative fat mass (RFM) and the prevalence of nonalcoholic fatty liver disease (NAFLD)
and severe hepatic steatosis (SHS). The authors report a positive, nonlinear association with
identifiable thresholds for RFM linked to increased disease prevalence. The study is based on a
large, nationally representative cohort, with robust statistical modeling and appropriate subgroup
analyses. It addresses a relevant clinical question using a novel adiposity index.
Major Concerns
• Causal inference limitation not sufficiently emphasized
While the cross-sectional nature is acknowledged, the manuscript language occasionally implies
causality (e.g., “RFM levels were positively associated with risk”). Stronger caution is warranted
in both the abstract and discussion to avoid misinterpretation.
• Inadequate handling of selection bias
The use of VCTE, which was performed voluntarily, could introduce selection bias. The authors
should provide more detail on how this may affect generalizability.
• Clinical implications remain vague
Despite identifying RFM thresholds, the practical utility of this information is unclear. How
these thresholds compare with current clinical cutoffs (e.g., BMI) or whether they improve
predictive capacity should be better discussed.
• Lack of external validation
The study could benefit from validation in a separate cohort, especially for the derived threshold
values of RFM. At minimum, the authors should mention this limitation explicitly and suggest
it as a future direction.
• Overadjustment in regression modeling
The fully adjusted Model 3 includes variables that may lie on the causal pathway (e.g., HbA1c,
CRP, ferritin). This could lead to overadjustment bias. Authors should discuss this limitation.
• Figures need improved labeling and clarity
Figures 1–3 (flowchart, curve fitting, and subgroup analysis) are hard to interpret without clearer
legends. For instance, Figure 2 lacks axis definitions and does not clearly explain what is meant
by the shaded area representing 95% CI.
Minor Concerns
• Terminology inconsistencies
The manuscript inconsistently uses “prevalence of NAFLD” and “risk of NAFLD.” Since this
is a prevalence-based study, all such statements should consistently use “prevalence” or “odds.”
• Statistical presentation
Some results in Table 3 and Table 4 are duplicated in the text with excessive decimal precision
(e.g., OR: 1.22, 95% CI: 1.18–1.26). It would be preferable to round to two significant digits
for readability.
• Missing information on missing data handling
It is unclear whether any imputation was used for missing covariates. The method of handling
missing data should be stated clearly.
• Redundancy in background section
The manuscript repeats general information about NAFLD multiple times in both the
Introduction and Discussion. The background could be shortened for better focus.
• Units missing in some variables
In Table 1, variables like CRP, ALT, and Alb lack units. These should be added for clarity #.
Limitations
• Potential misclassification of NAFLD/SHS due to VCTE thresholds
CAP thresholds are used instead of biopsy, which could lead to misclassification bias. Although
this is mentioned briefly, a deeper discussion is warranted.
• Lack of information on diet quality or physical activity
While sugar and energy intake are included, broader dietary patterns and lifestyle variables are
not considered, which could confound the association between RFM and liver disease.
• Sex-specific thresholds not explored
Although sex is adjusted for in RFM and subgroup analyses are conducted, the threshold analysis
did not report sex-specific thresholds. Given known sex differences in fat distribution, this is
a missed opportunity.
Language and Presentation
• The manuscript is well written overall, but some language revisions are necessary:
• Replace ambiguous terms like “risk” with “odds” or “association” when referring to cross-
sectional results.
• Avoid passive phrasing such as “NAFLD is diagnosed when…” and instead specify “In this
study, NAFLD was defined as…”
• Reword examples:
• “This study had several advantages.” # “This study presents several strengths.”
• “Therefore, our results accurately represent…” # “Thus, these findings reflect the prevalence
in the general adult U.S. population.”
assistant