Reviewer’s report
Title: 
The Association Between Sexual Orientation, BMI, Obesity Diagnosis,
and Provider Recommendation for Weight Management
Version: 
0 
Date: 
14 Jul 2021
Reviewer: 
Michèle Dramaix-Wilmet
Reviewer's report:
It's an interesting and original paper but there are some methodological problems
and the tables are not very clearly presented.
Abstract
The background explains that lesbian and bisexual women are more likely to be
overweight and obese, however, the study concerns only obese women and has a
different objective from the comparison of overweight and obesity in the two
groups of women. The introduction is clearer.
The conclusion should specify that it applies to obese women. For example,
"obese" could be added between "heterosexual" and "females" in the first
sentence. 
Introduction
Are all references 1-19 for lesbian or bisexual women? It's not often suggested
by the titles. I looked at two meta-analyses: references 6 and 16 but I didn't find
any results on lesbian or bisexual women; maybe I missed something. 
Methods
Abbreviations are not easy to understand when you are not familiar with the
laws of the United States. IRB (p. 5, line 48) is defined a few lines later (line 55)
a few words to explain HIPAA might help. The 1st paragraph of "Study design"
also appears in "Ethics approval", is it necessary to keep it in the text?
"Study design p.5": what was of proportion of patients excluded due in particular
because to missing sexual orientation? Were all patient files complete or were
files excluded because some sociodemographic variables or medical conditions
were missing? 
p. 6, lines38-41, "Matching". The following sentence (lines 41-48) seems to
indicate that there was no matching but that 3 controls were randomly chosen for
each "exposed" patient. Is there a reason to choose 3 controls? If there is really
matching, what are the matching criteria and was the matching taken into
account in the analysis? If there is no matching, why was a different control
group chosen for lesbian and bisexual?
A detail: the sentence p. 6, lines 41 to 48, could perhaps be simplified by
removing the two "of the 3,648 patients who identified as straight" as it is clear
that the straight women were randomly selected out of 3,648 patients who
identify as straight. 
What was the method used for random selection of controls? Simple random
sampling from the patient list or systematic sampling?
p. 7, line 19, "Data collection": again, a definition of the abbreviations would be
useful even though they are listed in Table 1. 
P7, line 53: why use Fisher exact for all analyses of association between
categorical variables; was not the Chi² valid?
p. 8; line 4: these transformations are not usual for BMI, how to interpret the
regression coefficients? Why not use quantile regression which easier to
interpret?
Statistical analysis: have the assumptions for linear regression, fit of logistic
models and absence of collinearity between variables included in the model been
checked? 
Results
Table 1: the table is not clear because there are too many columns. One column
for P-values is enough for each comparison, with footnotes indicating which test
was applied. The number of subjects for "Bisexual - Straight" (48-146) doesn't
correspond to that in the methodology: 49 -147 and there are therefore not
exactly 3 controls for each bisexual women.
Comment about the interpretation of table 1 (p.8, lines 41-43): the result of the
test (p=0.0083) refers to the comparison of the marital status distributions in the
two groups and not only to the comparison the proportions of "single"; there is
also a lower proportion of separated in Lesbian and the proportions of married
women are similar. 
Some categories have a very low number of subjects (race, ethnicity) and in
multivariable models, the 95%CI of the corresponding OR, are so large that they
are non-interpretable. These categories should be grouped with another one or
deleted (see comment on supplementary table 4).
Table 2: What's the number of subjects? 
P9, lines 33-44: it should be specified that this comment refers to Table 2.
Supplementary Table 2: the table is not clear, for example, it's difficult to read
the 95%CI, it is impossible to interpret the regression coefficients and scientific
notation is perhaps may not be easy for everyone to understand.
Supplementary Table 3: some OR are quite different in the two samples (lesbian
+ straight and bisexual + straight); for example, the OR for hypertension is 0.52
in the 1st sample and 2.16 in the second. How to explain this difference? The
same is truefor example in supplementary table 4 (OR=2.13 in 1st sample and
7.82 in 2nd sample) and in supplementary table 5 (OR = 1.6 in 1st sample and
6.27 in 2nd sample) for obesity. However, both samples consists of a majority of
random controls.
Supplementary Table 4: the upper limit of 95%CI is very high for "Other" race;
this is explained by the very small number of subjects in this category as shown
in Table 1. Is it not at least possible to group "Asian" and "other"? 
Comments on the form: the number of decimals should be standardized (for
example, P-values in table S3 are with 2 or 4 decimals, OR with 2 or 3 decimals,
OR with 3 decimals and 95%CI with 2 decimals…). The units of quantitative
variables should appear in the tables.
Discussion
There is no comparison with the literature in the discussion. Are there no
publications related to lesbian and bisexual healthcare that might be of interest?
Do the publications on obesity not analyse some factors such as treatment or
counselling?
Conclusion
Could the abbreviation USPSTF be defined?
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Is the study design appropriate to answer the research question (including the use
of appropriate controls), and are the conclusions supported by the evidence
presented?
Yes
Are the methods sufficiently described to allow the study to be repeated?
No
Is the use of statistics and treatment of uncertainties appropriate?
Yes
Is the presentation of the work clear?
No
Are the images in this manuscript (including electrophoretic gels and blots) free
from apparent manipulation?
Yes