Title: Association between blood heavy metals exposure with uterine fibroids among American
women: A cross-sectional analysis from NHANES data
Version: 1 Date: 10 Jul 2024
Reviewer's report:
The authors conducted an analysis in NHANES 1999-2006 of the associations of cadmium,
mercury, and lead measured in whole blood with reported diagnosis of uterine fibroids. This
research question has already been addressed using NHANES 1999-2002 data. Critiques are
discussed below.
Introduction:
1. Paragraph 1: The reference cited in the first sentence is not the most valid data on prevalence
of UF.
2. Paragraph 2 sentence 1: please correct “exposuring” to “exposure”
3. Paragraph 2 sentence 1: I think it is an overstatement to say that heavy metals may be “among
the most significant contributors to female reproductive health issues”.
4. Paragraph 2 sentence 2: Dietary intake is not the only route of exposure to heavy metals. I
suggest revising the first 2 sentences so that routes of exposure are described separately from
the health impacts.
5. Paragraph 2: Reference #13 does not seem like it provides primary evidence for the claim in
this sentence about heavy metals influencing HPG axis and alterations in sexual maturity and
functions.
6. Paragraph 3: As summarized here, reference #14 does not directly support the claim that
exposure to heavy metals contributes to fibroid development.
7. Paragraph 3: It is important to mention in the introduction that the association between heavy
metals and uterine fibroids in NHANES 1999-2002 data has been published previously, and to
clarify what the present analysis contributes.
Methods:
1. Study population: The relevant references to NHANES data should be cited.
2. Study population: A flow diagram showing participant inclusion/exclusion should be
provided.
3. Ethical considerations: Being anonymized does not mean that a study complies with ethical
standards. Also, it should be listed who “ethically approved” the NHANES study. Appropriate
information should be found on the NHANES website.
4. Independent variable: Were the lower limits of detection the same for each metal across the
NHANES cycles analyzed?
5. Covariates: Why dichotomize age at the median?
6. Covariates: Presumably, the analysis does not include males, so the categorization for alcohol
intake among males should be omitted.
7. Covariates: Why adjust for current pregnancy status? The fibroids diagnosis likely occurred
before the current pregnancy. Also, fibroids may affect the ability to become pregnant, so current
pregnancy is possibly downstream of the outcome, so adjusting for it is inadvisable.
8. Statistical analysis paragraph 1: “All variables were categorized into two distinct groups based
on the presence or absence of uterine fibroids.” What does this mean?
9. Statistical analysis paragraph 2: What is meant by “multilevel” logistic regression models?
Do you mean multivariable?
10. Statistical analysis paragraph 2: “factors such as” implies that there are other adjustment
variables not written there. This sentence should include all adjustment variables in the model.
11. Statistical analysis paragraph 3: it is unclear how these demographic factors were
“incorporated”.
12. The statistical approach for the subgroup analyses is unclear.
13. The analytic decisions for the spline curves should be described. What knots were used?
Were values truncated at any minimum or maximum value? Were alternative specifications
attempted? What adjustment variables were used?
Results:
1. General: I recommend de-emphasizing (or completely removing) p-values and statistical
significance, and instead focusing on the magnitude and precision of associations.
2. Demographic characteristics: Individuals without UF should not be described as “controls” in
this cross-sectional study. It is not a case-control study. I recommend describing the participants
as “women with fibroids” and “women without fibroids”.
3. Demographic characteristics: Percentages and means/medians would be much more
informative here than P-values.
4. Demographic characteristics: The report in the text that a higher proportion of white
individuals had fibroids is incorrect.
5. Table 1: Please report no more than 1 digit after the decimal place for percentages.
6. Table 2: The statistic should be listed in the table (are these medians and 25th, 75th
percentiles?) What statistical test was used for the comparisons? (although I would favor
removing the p-values altogether)
7. Correlation between...: The term “association” is more appropriate than “correlation” here,
as correlation suggests a pairwise Pearson or Spearman correlation.
8. The association of cadmium with fibroids in model 2 would be more accurately described
as a weak positive association. It should not be considered “no association” on the basis of not
being statistically significant.
9. Subgroup analyses: If this is to contribute meaningfully to the paper, revisions are needed.
The statistical methods and the rationale were not described clearly. For example, why should
mercury have a different effect on fibroids in women who are single vs. partnered? I recommend
focusing on a smaller number of subgroup factors, with clear biological rationale, and clarifying
the analytical approach and hypotheses.
Discussion:
1. Second paragraph: “For the first time, we pinpointed the blood toxic metals instrumental in
the development of uterine fibroids.” This claim is false, it overstates the contribution of the
present work and disregards the relevant literature.
2. The literature review on biological mechanisms for lead, cadmium, and mercury related to
fibroids was well done.
3. “Yet, a cohort with 1664 women aged 23-35 years observed an inverse correlation between
education, income, and blood Cd levels,(38) which is in accordance with our findings.” In what
way is this in accordance with your findings? I did not see a comparison of cadmium levels by
education and income in this paper.
4. Strengths: “innovative methods” were not applied. The analysis of various “interaction
factors” is not a strength without explaining the biological rationale. The RCS analysis was not
sufficiently explained to justify focusing heavily on 13.98 as a specific threshold to avoid.
5. Limitations: The limitation due to reliance on doctor diagnosis for the outcome data should
be mentioned. It is well known that uterine fibroids are underdiagnosed.