Reviewer’s report
Title: 
Factors associated with health-related quality of life in women using path
analyses: Mediation effect of the adiposity traits
Version: 
3 
Date: 
10 Aug 2021
Reviewer's report:
STATISTICAL REVIEWER ASSESSMENT: 
Is the study design appropriate for the research question (considering whether the
analyzed population accurately reflects the design and whether you see any
problems with control/comparison groups, e.g., likely confounders)?
Yes - overall design, population, and control groups are appropriate
Are methodologies adequate and well implemented (considering whether
assumptions are addressed and whether analyses are robust)?
No - there are minor issues
Are the analyses adequately communicated (considering whether reporting
details are adequate and whether figures and tables are well labeled and
described)?
No - there are minor issues
Does the interpretation accurately reflect the analyses without overstatement
(considering whether limitations/bias are acknowledged and whether accurate
descriptors, e.g., 'significant', are used)?
No - there are minor issues
Could an appropriately REVISED version of this work represent a statistically
sound contribution? 
Probably - with minor revisions
STATISTICAL REVIEWER COMMENTS:
Overall, I appreciate the authors' efforts in responding to my previous round of
concerns. 
I am mostly satisfied with the authors' responses, except the remaining
issues as follows:
1. I commented previously: "First and foremost, a fundamental and fairly critical
issue -- The authors mistakenly used scores (e.g., TEF-E; Three Eating Factor
Questionnaire-emotional score), instead of variables (e.g., age), in their
statistical analyses. To put it another way, the authors are conceptually wrong.
Hence, the relatively important Figure 2 is erroneous."
The authors responded: "Dear reviewer, as you know, path analysis is a subset of
Structural Equation Modeling (SEM), the multivariate procedure that, as defined
by Ullman (# Ullman JB, Bentler PM. Structural equation modeling. Handbook
of psychology. 2003 Apr 15:607-34.), "allows examination of a set of
relationships between one or more independent variables, either continuous or
discrete, and one or more dependent variables, either continuous or discrete." In
fact, a path model is specified entirely with observed variables, but the flexibility
allows for multiple independent observed variables and multiple dependent
observed variables. An independent observed variable is a raw score obtained
from a measurement instrument or assigned to an attribute variable
(#Schumacker RE, Lomax RG. A beginner's guide to structural equation
modeling. psychology press; 2004 Jun 24). So, we included the Three-Factor
Eating Questionnaire (TFEQ-R18) domain scores (Uncontrolled eating (UE),
Cognitive restraint (CR), Emotional eating (EE)) as independent observed
variables in the path model (Figure 2). We hope that this section is now much
clearer for reviewer.
First and foremost, I have no question/concern as regards the authors' use of path
analysis (indeed, it was the proper statistical technique to be carried out, as
pointed out in the previous round of review). 
Actually, my concern was the
authors mistakenly used scores in lieu of variables in the related tables and
figures of their paper. 
The authors provided the rebuttal -- "An independent
observed variable is a raw score obtained from a measurement instrument or
assigned to an attribute variable (#Schumacker RE, Lomax RG. A beginner's
guide to structural equation modeling. psychology press; 2004 Jun 24)."
Nonetheless, I beg to differ. 
The rebuttal was sourced from the ANSWERS TO
EXERCISES section of the textbook of Schumacker & Lomax, where the
original text was: "Question 3: Explain the difference between an independent
latent variable and an independent observed variable: An independent latent
variable is not directly measured, but is computed using multiple independent
observed variables. 
An independent observed variable is a raw score obtained
from a measurement instrument or assigned to an attribute variable." (p. 10)
Above all, the authors failed to differentiate between a variable and a score.
There are three basic and related concepts for measurement to happen: (1) the
object of measurement; (2) the property or quality that's being measured for it;
and (3) the kinds of values that could be used to represent amounts of this
quality or property. 
The property or quality that's being measured for an object is
called a variable. 
Values or scores are the numbers or labels we assign to
represent amounts of this quality or property.
(https://cehs01.unl.edu/aalbano/intromeasurement/mainch2.html) 
For example,
intelligence is a variable, and it is measured using IQ scores. 
You can NOT
declare "intelligence = scores", which is the manner used by the authors of this
analysis. 
Accordingly, both Figure 2 and Table 2 need amendment. 
Furthermore,
the first column heading was missing in Table 2.
2. I commented previously: "In response to my previous comment — 'Among
socio-demographic parameters, age was found to be indirectly and negatively
associated with MCS (B=-0.040; P= 0.050). 
It should be statistically
insignificant. — the authors revised the p-value slightly -- P = 0.049. 
It does not
make much sense since the revised p-value of 0.049 is marginally significant
only. 
A similar concern for "education was seen to be indirectly and positively
related to MCS (B=0.529; P= 0.045) (p. 9, lines 187-188). 
All in all, it would be
much better to provide 95% CI statistics as well."
The authors responded: "Thank you for comment. We have provided 95% CI for
all of relationships in Table 1 as requested."
However, the authors failed to deliver their promise (i.e., no 95% CI statistic was
presented).
3. 
The authors still wrongly displayed "Structural equation modeling" in the Key
words 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?
No
Is the use of statistics and treatment of uncertainties appropriate?
Yes
Is the presentation of the work clear?
Yes
Are the images in this manuscript (including electrophoretic gels and blots) free
from apparent manipulation?
Yes