Title: Association between bacterial vaginosis with human papillomavirus in the United States
(NHANES 2003–2004)
Version: 3 Date: 12 Oct 2023
Reviewer's report:
General Comments:  This is an interesting study assessing the association between BV and HPV
in women participating in the NHANES survey in twenty years ago.  Strengths include the use of
a population-based national survey, the collection of numerous potential confounders and effect
modifiers, and the use of laboratory-based definitions for BV and HPV infection.  Weaknesses
include the cross-sectional aspect of the study, and the presentation and interpretation of results
and conclusions, which at times did not accurately reflect the analyses conducted and study
findings.  Finally, there were numerous minor typos and formatting issues which detracted from
the manuscript.
Specific Comments:
Introduction.  It is not clear to me how the presence of BV might impact management of HPV
infections or cervical lesions.
Introduction.  It seems you could have a more recent reference than 2010 for how common
cervical cancer is globally, as there are yearly estimates.
Introduction – Rewording is needed for clarity with regards to “preventing cervical lesions” and
“cessation of persistent HR-HPV” as there is no direct treatment for HPV or to prevent HPV
infections from developing into cervical lesions.
Methods – NHANES is described in two different paragraphs with similar but varying
descriptions (ex: “nationally representative data” and “population-based data”.  Combining the
two descriptions would improve readability.
Methods – HPV detection methods refer to the NHANES website, but does not provide a URL
for this.  Please add this as a reference.  Perhaps there is an academic publication for the HPV
testing methods in NHANES as well.
Methods – Race.  You have grouped race into 4 categories: non-Hispanic white, 2: non-Hispanic
black, 3: Mexican American, and 4: other races).  Perhaps 3 is actually Hispanic (which is
more broad than Mexican-American)?  Further, this factor is actually a combination of race and
ethnicity, so please use that wording in throughout your manuscript (as you did in Table 1).
Methods.  Education – it is unclear what “other” education is, as all education levels should be
easily classified into groups of increasing education.
Methods – Income to Poverty ratio.  It is abbreviated as PIR, suggesting that it is in fact the
opposite ratio. It is sometimes referred to as Poverty to Income ratio also (Table 1).  Regardless,
it is not clear what data is used to calculate this factor.
Methods – It is not clear how “Borderline” diabetes is defined.
Statistical.  More detail is needed as to how you accounted for sample weights in your analysis.
Methods.  Missing data.  Many of your factors have substantial missing data.  How was this
accounted for in your multivariable regressions?  Given that you have a model including all
factors in Table 1, and Drinking and Smoking each have 20% missing data or greater, there is
concern that you will be leaving out a substantial proportion of your data with this approach
to the analysis.
Table 1.  Age is listed as mean and sd, but it appears that a 95% CI is listed, not the SD.  SD
would be better.
Table 1 and Results.  In Table 1 you present column results (percentage of women with and
without HPV who are in a certain group), not row results (percentage of women in certain group
who have HPV).  However, in your results narrative, you incorrectly have presented the data
as if the percentages were row percentages.  You state that “Notably,33.03% of non-Hispanic
black had HPV infection”.  This is not true.  It is that 33.03% of women with HPV were non-
Hispanic blacks.  The correct percentage would be 130/292 which is 44.5%  Given that HPV
is your outcome and this is a cross-sectional study, it seems that it would be easier to interpret
findings if you presented row percentages in Table 1 and in the results.
Results – Smoking – It’s not “who were more likely to smoke at least 100 cigarettes in a lifetime”
but those “who had smoked at least 100 cigarettes in their lifetime”.  Regardless, again you have
confused the interpretation of the percentages, reporting column percentages as if they were row
percentages.
Results/Figure 1.  The same issue is true of your BV results, which are incorrectly interpreted.
It is not true that “HPV positive was found in 64.24% of women with BV and 35.76% of those
without BV.”  It is true that BV was found in 64.24% of women with HPV.  HPV was found
in 424/767 (55.2%) of women with BV.
Results – Purpose and interpretation of stratified analyses.  You state that your approach was
to “to try to reveal the effect of confounding factors on HPV”.  However, your approach instead
would reveal not whether there was confounding but instead whether there was differential
impact by those factors (effect modification), which is a different concept.  Further, the
determination of effect modification should be based upon differential OR’s across the strata,
not the p-values, as p-values will be impacted greatly by sample sizes within strata.  For example,
you state that BV was associated with HPV only in those who did not smoke.  However,
risk estimates were nearly identical in those two strata (1.37 among smokers vs 1.48 in non-
smokers in univariate and the opposite (1.45 vs. 1.34 in multivariable analysis).  I would interpret
this as not have effect modification by smoking status and expect that in a model with an
interaction term, there would not be a significant interaction.  Interpretation (significance of EM/
interaction) can be assessed in your multivariable approach with an interaction term, so that you
can determine if differences by factors are significant.  Your analytic approach needs to match
your epidemiologic goals and the interpretation needs to match your analysis.
Discussion – You refer to the “strongest associations” as being in “in women younger than
20 years of age, in women with a BMI of > 25, and in non-Hispanic whites.”.  It is not clear
what the basis for that statement is.  It is true that you have the highest OR’s in those under 20
(OR=2.14) and women with BMI 25-30 (OR=1.88), but your OR’s in women with BMI 30+
(OR=1.57) and non-Hispanic whites (OR=1.40) are not especially high and for race/ethnicity,
are not even higher than those for other groups such as non-Hispanic blacks (OR=1.64) and
Hispanics (OR=1.65).  Further, you suggest later that the association may be impacted by age,
BMI, and ethnicity, even though you have not shown any significant differences by any of those
factors.  Later you state that the associations were present “particularly in white women and
women with a BMI of 25 or more”.  Again, you have little evidence of differential associations
across race/ethnicity or BMI, and if anything, your associations were stronger (higher ORs) in
non-white women.
Discussion – Interpretation of your results and temporal sequence. Your study is cross-sectional,
as are many of the studies referenced in your discussion.  You state that these studies suggest
that “the presence of BV increases the risk of cervical HPV infection.”.  However, this is too
strongly worded for these types of studies.  You do not know the order of infections in your
study, and BV could be a co-condition or come before or after HPV infection.  More appropriate
wording is that your study (and cross-sectional studies by others) show an association (which
may or may not be causal).
Discussion – Hierarchical model – you mention that you conducted a hierarchical analysis, but
this has different meaning, considering population level and then individual factors, than what
you conducted.  Please clarify your meaning using different terms.
References – The order is challenging, as it is neither in order of citation nor alphabetical.  It
appears that perhaps there are two sets of alphabetical references which contribute to this issue.
Minor comments:
Introduction – It seems there is a missing phrase: . We all know that human papillomavirus
(HPV) is the cause of cervical cancer, especially in high risk. (high risk what?)
Introduction – It is unclear what “following reproductive tract” means – please reword for clarity.
Introduction – ‘studies have”…  needs a capitalization at the beginning of the sentence.
Introduction - Punctuation needs correcting around the references: “(Feng et al., 2018). (Ghosh
et al., 2017)(Gillet et al., 2012).”
Methods – spacing is needed – BV Score0-3.
Methods and throughout the manuscript – Indentation and spacing of paragraphs and sections
varies throughout.
Table 1 – Negative and Positive are both incorrectly spelled.
Table 1 and 2 – The titles should be more descriptive and could include the data source, sample
size, years, etc.
Discussion – there are numerous small typos throughout (NHANES needs capitalization, some
sentences begin without capitalization, etc).