Title: Association between blood heavy metals exposure with uterine fibroids among American
women: A cross-sectional analysis from NHANES data
Version: 2 Date: 23 Dec 2024
Reviewer's report:
"PEER REVIEWER ASSESSMENTS:
OBJECTIVE - Full research articles: is there a clear objective that addresses one or several
testable research questions? (Brief or other article types: is there a clear objective?)
No - there are minor issues
DESIGN - Is the current approach (including controls and analysis protocols) appropriate for
the objective?
No - there are minor issues
EXECUTION - Are the experiments and analyses performed with sufficient technical rigor to
allow confidence in the results?
No - there are minor issues
STATISTICS - Is the use of statistics in the manuscript appropriate?
Yes - appropriate statistical analyses have been used in the study
INTERPRETATION - Is the current interpretation/discussion of the results reasonable and not
overstated?
No - there are minor issues
OVERALL MANUSCRIPT POTENTIAL - Has the author addressed your concerns sufficiently
for you to now recommend the work as a technically sound contribution? If not, can further
revisions be made to make the work technically sound?
Probably - with minor revisions
PEER REVIEWER COMMENTS:
GENERAL COMMENTS: This study effectively examines the association between heavy
metal exposure and uterine fibroids using robust statistical methods, including weighted
logistic regression, RCS, and BKMR models. The identification of mercury (Hg) as a key
contributor, alongside lead (Pb) and cadmium (Cd), provides valuable insights into the
environmental determinants of uterine fibroids. The stratified analysis highlights the influence
of age, marital status, and combined heavy metal exposures, offering nuanced perspectives on
vulnerable populations. However, the study's cross-sectional design limits causal inference, and
reliance on self-reported fibroid diagnoses may underestimate prevalence. The discussion of
biological mechanisms is thorough, though occasionally dense and speculative. While the study
underscores the importance of monitoring heavy metal exposure, it falls short of proposing
concrete public health or clinical interventions. Despite these limitations, the findings are
significant, emphasizing the need for further longitudinal research and heightened awareness of
environmental toxins' impact on women's health. This work makes an important contribution to
understanding uterine fibroids' etiology and environmental risk factors.
For the sake of clarity, I declare that I am reviewing the revised version of this paper, although I
was not reviewer for the first submitted version. The authors addressed the previous reviewers’
comments.
REQUESTED REVISIONS:
I recommend to take into account the following suggestions:
- Introduction: Inconsistencies in Grammar and Syntax: Several grammatical and typographical
errors detract from readability. For example: ""well-beingj"" should be ""well-being."";
""further exacerbating the quality of life for affected wome"" should read ""women.""; ""clinical
practice and the development of preventive strategies to alleviate the burden associated with this
prevalent reproductive health condition"" could be streamlined for conciseness.
- Introduction: Some sentences are overly dense or lack flow, making the introduction harder
to follow. For instance, the section discussing dietary exposure to heavy metals could be
reorganized for better readability and to avoid redundancy.
- Introduction: The prevalence of uterine fibroids is stated as ""5.8% (US),"" but the reference
or methodology behind this statistic is unclear. Providing more context about the data source
would enhance credibility.
- Introduction: While the knowledge gap is well-identified, a clearer articulation of the specific
research question or hypothesis would strengthen the study's framing.
- Introduction: The introduction mentions inconsistent results in previous studies but does not
elaborate on these inconsistencies or offer examples of conflicting findings. This would provide
a more robust context for the study.
- Methods: The section is dense and could benefit from improved organization. Dividing it
into subsections with clear headers (e.g., ""Study Design,"" ""Data Collection,"" ""Variable
Definitions,"" ""Statistical Analysis"") would improve readability.
- Methods: While the covariates are described in detail, their inclusion rationale (e.g., why certain
demographic or lifestyle variables were chosen) could be more explicitly stated.
- Methods: Certain terms like ""Poverty Income Ratio (PIR)"" and ""Bayesian Kernel Machine
Regression (BKMR)"" are introduced without sufficient explanation for readers unfamiliar with
them. A brief explanation or a reference would aid comprehension.
- Methods: While demographic and lifestyle factors are included, other potential confounders
(e.g., occupational exposure, environmental pollution) are not addressed. Justification for their
exclusion is warranted.
- Methods: Adjustments in Model 2 are described as including the same demographic variables
as Model 1, raising questions about their differentiation. Clarify if additional covariates or
interaction terms were included.
- Methods: The section does not provide enough detail on how BKMR was implemented (e.g.,
convergence diagnostics, number of iterations for Markov Chain Monte Carlo). Adding these
details would enhance transparency.
- Methods: The exclusion of participants with missing data could introduce bias. A discussion
on how this might affect generalizability is missing.
- Methods: The section does not describe any cross-validation or external validation to test the
robustness of the models used.
- Results: The presentation of logistic regression results is dense and could be better structured.
Highlighting key trends or notable differences between models in a summary paragraph would
improve clarity.
- Results: The rationale for specific subgroup categorizations (e.g., why the median was used
for Hg levels) is not clear and should be justified.
- Results: The adjustment process for covariates across models is described but not fully
explained regarding why specific variables were included or excluded in each model.
- Results: It is unclear whether multicollinearity among covariates was assessed, particularly
given the complex regression models.
- Discussion: Some sections, especially on biological mechanisms (e.g., Pb and Cd pathways),
are overly detailed, making the discussion dense and hard to follow. Streamlining these
explanations while retaining essential details would improve readability.
- Discussion: The section on Hg-related findings is insightful but somewhat repetitive. The
narrative could be condensed to focus on key points.
- Discussion: While the study acknowledges variability in results from previous research, it
lacks a detailed comparison of how the current findings align or contrast with specific studies.
For example, discrepancies in Hg-fibroid associations across different cohorts are not fully
contextualized.
- Discussion: The role of age and marital status as moderators of Hg exposure is discussed, but
the underlying mechanisms (e.g., shared environmental exposures, stress) are speculative and
would benefit from more evidence or clearer acknowledgment of the gaps.
- Discussion: The limitations section is thorough but would benefit from prioritizing the most
critical issues, such as the cross-sectional design and reliance on self-reported fibroid diagnosis.
Some points, like the lack of data on lifestyle factors, could be condensed or moved to a broader
discussion on potential confounders.
- Discussion: While the use of advanced statistical models is a strength, the discussion does
not adequately address the limitations of these methods, such as potential overfitting or the
interpretability of PIP values in the BKMR model.
- Discussion: Although the study emphasizes the need for heavy metal monitoring, it lacks
specific recommendations for policy changes or clinical practices, such as improved dietary
guidelines, environmental regulations, or routine screening for heavy metals in high-risk
populations.
- Discussion: Suggestions for future research are limited to methodological improvements (e.g.,
longitudinal studies) and could benefit from a broader scope, such as exploring interventions to
mitigate heavy metal exposure or understanding regional disparities in exposure risks."