Reviewer’s report
Title: 
Cancer prevention in females with and without obesity – Does perceived
and internalised weight bias determine cancer prevention behaviour?
Version: 
0 
Date: 
08 Nov 2020
Reviewer: 
Panayotis Constantinou
Reviewer's report:
In this work, the authors investigate recommended cancer screening uptake in
women with obesity, using self-reported survey data. More specifically, the
objectives of this study are to compare cervical, breast and colorectal cancer
screening behavior between obese and non-obese women and to analyze
determinants of cancer screening behavior among obese women, focusing on
experienced and internalized weight bias.
Although the research question is of great interest and the paper is clearly
structured, I believe that it is not adequate for publication in its current form,
because of potential methodological flaws. Please note that my expertise lies
more on methodology and health system organization than on clinical or
psychological aspects. However, if some methodological issues are not taken
into account, results on weight bias cannot be correctly interpreted.
Measures of cancer screening behavior
1) In measuring utilization of screening services, authors must make sure that
reported utilization (for mammography and colonoscopy) is not related with
current diagnosis of the corresponding cancer. Cancer awareness is an important
determinant of screening behavior but including personal cancer diagnosis may
misclassify a diagnostic procedure into preventive practice. In Table 5,
comparing the effects of "cancer diagnosis" and "CPS knowledge" variables may
indicate such misclassification bias.
2) Another classification issue is related to the Pap smear sufficient utilization
variable: a woman aged 35 and more with a smear test every three years has
recommended screening practice (Table 2) but will be classified as "insufficient
utilization" (In Table 4, some women among the 19% with obesity and less than
one smear test a year may have sufficient utilization). This issue concerns more
than 90% of the study population (93%, Table 3). 
Comparison of screening uptake between obese and non-obese women
3) The validity of the results reported in Table 4 (page 10, line 242 to page 11,
line 267) can be questioned if study samples of women with and without obesity
are not comparable regarding known screening determinants. For example, Table
3 indicates that obese women have lower academic education (46.4% vs 64.6%
in highest category) and lower household income (12.7% vs 19.6% in highest
category). Authors should report in Table 3 all screening determinants measured
(including insurance status and cancer awareness) and compare the distributions
of these variables between the two study samples. 
4) One solution could be to compute logistic models for each screening practice
within the entire study population and to include obesity among explanatory
variables. The adjusted effect of obesity on each screening practice could be
interpreted. Another advantage of this option would be to introduce BMI as a
categorical variable and assess if there is a gradient between BMI and preventive
practices. 
Analysis of screening uptake determinants among women with obesity
5) The specification of the variables included in the logistic models seems
problematic. Introducing categorical variables (WB, WBIS, income, education)
and age as continuous variables results in assumptions about the effect of the
variables on the outcomes that are most probably false. Usual practice would be
to introduce them in the model as categorical variables, defining a reference class
for each variable and estimating one OR for every remaining class. 
6) Sample sizes for colorectal cancer screening (n=336 and n=252) are smaller
than the mammography group (n=340) despite larger age eligibility range. If the
number of women excluded because of missing data is important, the estimated
effects could suffer from selection bias. Sensitivity analyses including a
"missing" category could be useful to assess stability of the results.
7) Have you tested to include screening behavior for one cancer location to
models on screening behavior of the other cancer locations (when applicable
according to age eligibility)? 
Interpretation of screening uptake determinants according to cancer location 
8) Interpreting weight bias and internalized weight bias according to the type of
cancer screening is of interest for understanding barriers to recommended
preventive practice among obese women. You mention that all services are
financed by health insurance (page 3, line 73) but more contextual information
could be informative: are all services free of charge both for public and private
coverage? Are there any other programs, such as organized screening, that could
differentially influence uptake? If it is the case, adding a column in Table 1 with
this information could maybe be useful.
Additional general comments
9) How could you take into account or discuss the discordance between BMI and
perceived weight status in Table 3 (13% of obese women self-perceived as
normal or slightly overweight and >60% self-perceived as non-obese)?
10) Because of potential limited sample sizes for some categories, it would be
better to systematically report both detailed sample sizes (not only global) and
percentages in Table 4.
11) I believe you could also discuss results with p values between 0.05 and 0.10
(Tables 4 and 5), especially if they are consistent with the results statistically
significant at the 0.05 threshold. 
12) Some additional details about the survey design and especially about
selection of women with obesity could be useful in the Methods section.
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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?
No
Are the methods sufficiently described to allow the study to be repeated?
Yes
Is the use of statistics and treatment of uncertainties appropriate?
No
Is the presentation of the work clear?
Yes
Are the images in this manuscript (including electrophoretic gels and blots) free
from apparent manipulation?
Yes