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PEER REVIEW HISTORY
BMJ Open publishes all reviews undertaken for accepted manuscripts. Reviewers are asked to
complete a checklist review form (http://bmjopen.bmj.com/site/about/resources/checklist.pdf) and
are provided with free text boxes to elaborate on their assessment. These free text comments are
reproduced below.
ARTICLE DETAILS
TITLE (PROVISIONAL)
AUTHORS
Prevalence, Associated Factors and the Heritability of Metabolic
Syndrome and its Individual Components in African Americans: The
Jackson Heart Study
Khan, Rumana; Gebreab, Samson; Sims, Mario; Crespo, Pia; Xu,
Ruihua; Davis, Sharon
VERSION 1 - REVIEW
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Roy T. Sabo
Virginia Commonwealth University, United States of America
23-Jun-2015
The authors have presented their findings from a study of the
prevalence of MetS in African American participants in the Jackson
Heart Study. They are to be commended for addressing this topic,
as this group has been severely understudied in the existing
literature. The methods and approach taken by the research team
are sound and defensible. The comments and concerns I have
(listed below) are focused mainly on methodological transparency.
Specific Comments:
1. Methods Section, Data Source, Last Sentence: Out of 5227 total
participants, the heritability analysis was conducted on 1636
participants from 281 families. The authors should break down
(either here or in the Results Sections) what types of family
members are included (siblings only?, parents and children?,
mothers, fathers, sisters, brothers, cousins?, etc.). This information
is highly necessary for gauging the heritability analyses (more on
this below).
2. Methods Section, Measures, 2nd Paragraph, First Sentence:
please replace the semicolon with a comma.
3. Methods Section, Measures, 2nd Paragraph, 2nd Sentence:
Education status is listed as having 3 categories, but only one is
listed. Please provide all three here.
4. Results Section, Tables: Please report all percentages to 1
decimal point (36.52% tells the reader nothing that 36.5% does
sufficiently). Likewise, please report all ages to 1 decimal point.
5. Results Section, Table 1: Given that the primary analysis is
conducted separately for males and females, I'm not sure that Table
1 is necessary. Especially since a lot of this material is provided in
Table 2 through the lens of having MetS or not, I don't see much
value in Table 1. Please consider removing it.
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6. Manuscript: Please capitalize the "T" in "Table".
7. Table 3: The "1" for the reference cells looks a little odd. Please
consider replacing this with the phrase "Reference Level", which
more descriptively tells the reader what you've done in your model.
8. Table 4: Please consider a more descriptive column heading than
"Variations explained by covariate", something like "Proportion of
Outcome variation explained by covariates".
9. Heritability Analysis I: Given that previous results were conducted
separately for males and females, I wonder if the authors considered
conducting the Heritability analyses separately for each sex. I
understand that this could be problematic given families having
members of both sexes, but some explanation as to why these
analyses were conducted overall would be helpful to the reader.
10. Heritability Analysis II: Reading the heritability analysis makes
me wonder how these individuals are related, as no description has
been provided. Knowing how these individuals are related would put
the results listed in Table 4 and described at the end of the results
section into greater context.
11. Heritability Analysis III: This is the most critical comment I have
of the manuscript, in that the authors refer to "genetic" effects
throughout the manuscript. As genes were not analyzed, the authors
CANNOT state that the effects they estimated in Table 4 (so called
"Heritability Estimates") are in fact inherited. As they mention
themselves in the Discussion, an alternative and possibly competing
effect could be through cohabitation, simply living with others and
learning their behaviors. The analyses and results presented hear
cannot distinguish between genetic and cohabitation, and as such
the authors should either redefine heritability to include include both
genetic and cohabitation factors, or they should use a new term.
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Stefano Omboni
Italian Institute of Telemedicine, Italy
24-Jun-2015
The paper is interesting and well written. I have some remarks which
might help improving the quality of the presentation.
How was BP measured? By the auscultatory method? With a
mercury or aneroid meter? Please, detail.
There is one important factor which is missing: the type of
occupation. Can authors explain why they did not evaluate this
factor and the limitation of not including this factor in the model?
There is no mention on the methodology for collection and analysis
of CRP, adiponectin and homocysteine. Were these measures
collected at the time of the other ones or in separate occasions?
Which time interval occurred (if any) between the drawing of the
different samples?
Apparently, a logistic regression analysis forcing all variables in the
model was performed. I wonder whether results would change if a
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more objective analysis, based on a stepwise approach, would have
been performed.
Heritability analysis. Description is complex and hard to understand.
Maybe, because I am not familiar with this technique. Could authors
simplify for the standard reader?
Table 1. A column with summary data for the whole population
would be helpful.
Discussion. Maybe authors can compare the absolute prevalence of
Mets in their sample with other ethnic groups in the US (e.g.
Caucasian, Hispanic, etc.). This would be helpful for the reader.
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Sheila Barrett
Northern Illinois University, USA
02-Jul-2015
General Comments: Overall quality is acceptable, large sample size,
in-depth statistical analyses performed. Publication recommended
after minor revisions. The objectives of the study are not explicitly
stated in the background and significance portion. Conclusion,
recommendations and implications can be improved to make the
study seem really worthwhile doing. The authors said data collection
methods are described elsewhere but a brief statement on what
classification was used for MetS would help, the IDF stresses the
inclusion of high WC with any other 2 factors.
Specifics:
1. Page 5- line 37- remove the past tense from overestimate.
2. Page 6- Objectives need to be explicitly stated.
3. Page 7- Under measures, the authors used fasting “blood’
glucose then the abbreviation FPG followed here and
throughout the rest of the manuscript. Change this on page
7 line 35 to fasting plasma glucose if that’s what was
measured.
4. Page 7- line 39- write out waist circumference then
abbreviate.
5. Page 8- sentence on educational status- say what the other
2 categories were.
6. Page 8- line 20- remove “which is” and read as … Global
Perceived Stress Scale, an 8-item questionnaire…
7. Page 8- line 29- pluralize index as indices.
8. Page 8- line 34- sentence is awkwardly stated… replace
with “if they had stopped drinking for more than a year”
9. Page 8- line 39- need hyphen for C-Reactive protein (CRP
mg/dL)
10. Page 8- Add something here about medication use since
that was mentioned in the results.
11. Page 8- line 53- hyphen needed for t-test here and
remainder of document.
12. Page 9- add statement about statistical level that was
considered significant and the statistical package software
that was used. Was the SOLAR used just for heritability
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analyses or was this the package used for all analyses?
13. Page 10- Line 6- re-word to “Of the 5227 individuals …”
14. Add ± sign then give the SD … mean age was 53.93 ±12.93
and 55.30 ± 12.76 respectively for men and women.
15. Page 10- line ten- remove “according to characteristics
presented in table 1”. Start sentence at Educational level
were similar for men and women. See Table 1.
16. Page 10 – line 15- change in alcohol to “for” alcohol use.
17. Remove excessive vertical lines from tables to make them
look more professional. See example below. Table title
could be better stated. “ Characteristics of Participants of the
Jackson Heart Study by Gender (N= 5227)”
Variables
Men
Women
n = 1909
n= 3318
P value
Age
Metabolic
Syndrome
18. Page 16- discussion- start this off with a reminder of what
the current study was about.
19. State explicitly what factors were significant for the women
instead of saying “ in addition to these factors”
20. Page 17- paragraphing needed at line 32 (Literature have
indicated...) and 51 (Although lifestyle…)
21. Page 18- line 11- change “like” to such as different sample
size…
22. Page 18- lines 13- 23- needs some transitioning here, these
studies are just mentioned, need the sentences to flow so
reader can see what is important about the 4 studies alluded
to here.
23. Page 18- line 41- remove references 10-14, 19 and place
after … different studies…
24. Page 20- line 10- not sure ascertainment is the best word for
this, do you mean assessment?
25. Conclusion and recommendation are all mixed into one, try
to make the conclusion more explicit then make some
recommendations.
26. State the strengths of the study then the limitations after.
27. Make the implications of these findings stronger.
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VERSION 1 – AUTHOR RESPONSE
Reviewer: 1
Reviewer Name Roy T. Sabo
Institution and Country Virginia Commonwealth University, United States of America
Please state any competing interests or state ‘None declared’: None Declared
Please leave your comments for the authors below The authors have presented their findings from a
study of the prevalence of MetS in African American participants in the Jackson Heart Study. They
are to be commended for addressing this topic, as this group has been severely understudied in the
existing literature. The methods and approach taken by the research team are sound and defensible.
The comments and concerns I have (listed below) are focused mainly on methodological
transparency.
Specific Comments:
1. Methods Section, Data Source, Last Sentence: Out of 5227 total participants, the heritability
analysis was conducted on 1636 participants from 281 families. The authors should break down
(either here or in the Results Sections) what types of family members are included (siblings only?,
parents and children?, mothers, fathers, sisters, brothers, cousins?, etc.). This information is highly
necessary for gauging the heritability analyses (more on this below).
Authors’ response
Estimating heritability using variance component method (what we did) can only be done if an
extended pedigree file is available. Thus, it is implied that the family structure in the JHS was
complex, which we have also mentioned in the study strength section. However, we agree with the
reviewer that a more explicit description in the method section about the family structure of JHS might
be helpful. So, we added the following in the “Data Source” section:
“The family study component of JHS contained 1st degree (parent-offspring and siblings), 2nd degree
(grandparent-grandchild, avuncular, half-siblings) and 3rd degree or more distant (great grandparentgrandchild, grand avuncular, half avuncular, first cousins, half first cousins, second cousins) family
members.”
2. Methods Section, Measures, 2nd Paragraph, First Sentence: please replace the semicolon with a
comma.
Done
3. Methods Section, Measures, 2nd Paragraph, 2nd Sentence: Education status is listed as having 3
categories, but only one is listed. Please provide all three here.
Done
4. Results Section, Tables: Please report all percentages to 1 decimal point (36.52% tells the reader
nothing that 36.5% does sufficiently). Likewise, please report all ages to 1 decimal point.
Authors’ response
We agree. But in table 3 and in table 4, two decimal points should be reported. To be consistent with
that, we have reported all the percentages to two decimal points as well.
5. Results Section, Table 1: Given that the primary analysis is conducted separately for males and
females, I'm not sure that Table 1 is necessary. Especially since a lot of this material is provided in
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Table 2 through the lens of having MetS or not, I don't see much value in Table 1. Please consider
removing it.
Authors’ response
We also thought about the usefulness of this table, but at the end we decided to keep it as we think, it
will give provide the general characteristics of the study population, not through the lens of having any
diseases (MetS here) or not.
6. Manuscript: Please capitalize the "T" in "Table".
Done
7. Table 3: The "1" for the reference cells looks a little odd. Please consider replacing this with the
phrase "Reference Level", which more descriptively tells the reader what you've done in your model.
Agreed and done.
8. Table 4: Please consider a more descriptive column heading than "Variations explained by
covariate", something like "Proportion of Outcome variation explained by covariates".
Agreed. However we think, mentioning “outcome” is not necessary. It is implied. So instead we
changed it to “Proportion of variation explained by covariates”
9. Heritability Analysis I: Given that previous results were conducted separately for males and
females, I wonder if the authors considered conducting the Heritability analyses separately for each
sex. I understand that this could be problematic given families having members of both sexes, but
some explanation as to why these analyses were conducted overall would be helpful to the reader.
Authors’ response
The reviewer has rightly pointed out here that given the extended pedigree structure, separating them
by gender wasn’t always possible. Here is how an extended pedigree file could look like:
Fam id id father id Mother id Sex
12002
13001
14001
19412
1 13 4 1 1
1 19 4 1 1
1 21 3 2 2
1 22 0 0 1
1 23 22 21 1
22002
2 3 27 26 1
2 26 0 0 2
2 27 0 0 1
2 31 0 0 2
2 33 50 31 1
2 34 49 31 2
That is, if we want to do it only for females, we will need the information on their father too.
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We rather used gender as a covariate in our heritability analysis model.
10. Heritability Analysis II: Reading the heritability analysis makes me wonder how these individuals
are related, as no description has been provided. Knowing how these individuals are related would
put the results listed in Table 4 and described at the end of the results section into greater context.
Authors’ response
Estimating heritability using variance component method (what we did) can only be done if an
extended pedigree file is available. Thus, it is implied that the family structure in the JHS was
complex, which we have also mentioned in the study strength section. However, as the reviewer
suggested, we added the following in the “Data Source” section:
“The family study component of JHS contained 1st degree (parent-offspring and siblings), 2nd degree
(grandparent-grandchild, avuncular, half-siblings) and 3rd degree or more distant (great grandparentgrandchild, grand avuncular, half avuncular, first cousins, half first cousins, second cousins) family
members.”
11. Heritability Analysis III: This is the most critical comment I have of the manuscript, in that the
authors refer to "genetic" effects throughout the manuscript. As genes were not analyzed, the authors
CANNOT state that the effects they estimated in Table 4 (so called "Heritability Estimates") are in fact
inherited. As they mention themselves in the Discussion, an alternative and possibly competing effect
could be through cohabitation, simply living with others and learning their behaviors. The analyses
and results presented hear cannot distinguish between genetic and cohabitation, and as such the
authors should either redefine heritability to include include both genetic and cohabitation factors, or
they should use a new term.
Authors’ response
Yes. It is true that this is not a Genetic (I am assuming the reviewer meant GWAS or any Single
polymorphism association study when he said, “As genes were not analyzed“) association study. We
didn’t report if any genetic variant was associated with the traits. Rather, we estimated heritability and
heritability is defined as: “the proportion of the phenotypic variance in a trait that is attributable to the
additive effects of genes”
If we go into little more detail (Reference: http://www.nature.com/scitable/topicpage/estimating-traitheritability-46889)
All instances of phenotypic variance (VP) within a population are the result of genetic sources (VG)
and/or environmental sources (VE). This relationship can be summarized as follows
VP = VG + VE
Genetic sources of variation can themselves be divided into several subcategories, including additive
variance (VA), dominance variance (VD), and epistatic variance (VI).
Together, the values for each of these subcategories yield the total amount of genetic variation (VG)
responsible for a particular phenotypic trait:
VG = VA + VD + VI
The first subcategory, additive genetic variance, refers to the deviation from the mean phenotype due
to inheritance of a particular allele and this allele's relative (to the mean phenotype of the population)
effect on phenotype.
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The second subcategory, dominance genetic variance, involves deviation due to interactions between
alternative alleles at a specific locus.
Finally, like dominance variance, the third category of genetic variance—epistatic variance—involves
an interaction between alleles; however, in this case, the alleles are associated with different loci.
We estimated the mean or the additive genetic variance through heritability estimates and that is why
we have often referred it as “genetic” effect/contribution/variation/influence.
We however, have not gone into detail discussion about heritability in the paper as it is a research
article.
Inheritance (heritability estimates) of any trait is due to both, genetic effects, and of course shared
environment as the reviewer mentioned. We have acknowledged in our limitations that we couldn’t
account for shared environmental factors:
“Though we have accounted for important individual covariates, our heritability estimates were
influenced by shared environmental factors like childhood environment and neighborhood factors, and
thus, our results could be slightly overestimated”
That is, we used the following model to calculate the heritability (Additive genetic variance)
p= µ+ ∑βiXi + a+ e
Where, μ=Baseline mean, β=Regression coefficients, x=Scaled covariates, a=Additive genetic effects,
e=Random environmental effects
This model assumes that the only source of correlation among family members is genetic and do not
consider the shared environmental factors.
If we had information about the shared environmental factors our model would have been like
p= µ+ ∑βiXi + a+ c+ e
Where, μ=Baseline mean, β=Regression coefficients, x=Scaled covariates, a=Additive genetic effects,
c=Shared environmental effects, e= Random environmental effects
That is why our estimates could be overestimated.
Thus we believe, we CANNOT say the effect of any specific gene (out of 20,000-25,000 functional
genes) on our traits as we did not do any association study. But we think that we CAN mention about
the overall genetic effect/variance/influence. Because that is what we have calculated by heritability
estimates.
Here are few references to further clarifications:
http://www.nature.com/scitable/topicpage/estimating-trait-heritability-46889
http://www.ncbi.nlm.nih.gov/books/NBK21866/
http://www.ncbi.nlm.nih.gov/pubmed/12578801
http://www.ncbi.nlm.nih.gov/pubmed/19372593
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1289275/
Reviewer: 2
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Reviewer Name Stefano Omboni
Institution and Country Italian Institute of Telemedicine, Italy
Please state any competing interests or state ‘None declared’: None declared
Please leave your comments for the authors below The paper is interesting and well written. I have
some remarks which might help improving the quality of the presentation.
How was BP measured? By the auscultatory method? With a mercury or aneroid meter? Please,
detail.
Authors’ response
We have added the name of the instrument in our method section:
“Sitting BP was measured twice at 5-min intervals with standardized Hawksley random-zero
sphygmomanometer, and the average of two measurements was used”
There is one important factor which is missing: the type of occupation. Can authors explain why they
did not evaluate this factor and the limitation of not including this factor in the model?
Authors’ response
It is true that occupation is one important measure of socioeconomic status of an individual and can
be important in determining health of an individual. However, there are a number of occupations and it
is extremely difficult (and probably not necessary) to account for all of them in a statistical model. That
is why, researchers use either income or education in an industrial county setting as a proxy of
occupation. We used education and believe that in our population education gives an overall idea of
socioeconomic status of an individual.
There is no mention on the methodology for collection and analysis of CRP, adiponectin and
homocysteine. Were these measures collected at the time of the other ones or in separate
occasions? Which time interval occurred (if any) between the drawing of the different samples?
Authors’ response
Agreed. And we added the following in the “data Source” section:
“The current study data were obtained from the baseline clinic visit during 2000-2004”.
Apparently, a logistic regression analysis forcing all variables in the model was performed. I wonder
whether results would change if a more objective analysis, based on a stepwise approach, would
have been performed.
Authors’ response
We wanted to keep all the variables in the model not only the STATISTICALLY significant ones. That
is why, we have done the regression with all the variables. And if we had taken the stepwise
approach, the final model would anyway be the same as ours.
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Heritability analysis. Description is complex and hard to understand. Maybe, because I am not familiar
with this technique. Could authors simplify for the standard reader?
Authors’ response
Heritability is defined as: “the proportion of the phenotypic variance in a trait that is attributable to the
additive effects of genes”
If we go into little more detail: (http://www.nature.com/scitable/topicpage/estimating-trait-heritability46889)
All instances of phenotypic variance (VP) within a population are the result of genetic sources (VG)
and/or environmental sources (VE). This relationship can be summarized as follows
VP = VG + VE
Genetic sources of variation can themselves be divided into several subcategories, including additive
variance (VA), dominance variance (VD ), and epistatic variance (VI).
Together, the values for each of these subcategories yield the total amount of genetic variation (VG)
responsible for a particular phenotypic trait:
VG = VA + VD + VI
The first subcategory, additive genetic variance, refers to the deviation from the mean phenotype due
to inheritance of a particular allele and this allele's relative (to the mean phenotype of the population)
effect on phenotype.
The second subcategory, dominance genetic variance, involves deviation due to interactions between
alternative alleles at a specific locus.
Finally, like dominance variance, the third category of genetic variance, epistatic variance, involves an
interaction between alleles; however, in this case, the alleles are associated with different loci.
We estimated the mean or the additive genetic variance through heritability estimates.
We have not gone into details in the paper as it is a research article and not a technical paper.
However,
We have added atleast what heritability means in the analysis section now:
“After checking the pedigree data for inconsistencies a total of 1636 individuals from 281 families
were analyzed to calculate the heritabilities by variance component methods using SOLAR
(Sequential Oligogenic Linkage Analysis Routines) software to quantify the proportion of the variance
in MetS and in its individual components that was attributable to the additive effects of genes”
Here are few references to understand it further:
http://www.nature.com/scitable/topicpage/estimating-trait-heritability-46889
http://www.ncbi.nlm.nih.gov/books/NBK21866/
http://www.ncbi.nlm.nih.gov/pubmed/12578801
http://www.ncbi.nlm.nih.gov/pubmed/19372593
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1289275/
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Table 1. A column with summary data for the whole population would be helpful.
Instead of a simple descriptive table, we wanted to present the characteristics by gender and show if
they differed by using a t test or a chi square test. Significant p values in most of the cases justify our
presentation manner.
Discussion. Maybe authors can compare the absolute prevalence of Mets in their sample with other
ethnic groups in the US (e.g. Caucasian, Hispanic, etc.). This would be helpful for the reader.
We are assuming the reviewer here means overall prevalence (not sex stratified) of MetS by absolute
prevalence. We however, have not estimated that as we wanted to present the characteristics of our
sample by gender and show how they differed.
Reviewer: 3
Reviewer Name Sheila Barrett
Institution and Country Northern Illinois University, USA
Please state any competing interests or state ‘None declared’: NONE
Please leave your comments for the authors below See Attached file
Authors’ response
Please see the attached pdf file “response to reviews contd”
VERSION 2 – REVIEW
REVIEWER
REVIEW RETURNED
Roy T. Sabo
Virginia Commonwealth University
09-Jul-2015
GENERAL COMMENTS
The reviewer completed the checklist but made no further
comments.
REVIEWER
Stefano Omboni
Italian Institute of Telemedicine, Italy
11-Jul-2015
REVIEW RETURNED
GENERAL COMMENTS
The paper has been modified according to most of my indications.
However, I a couple of remarks have not been answered
appropriately. I kindly ask to clarify.
1. Original reviewer’s remark: Apparently, a logistic regression
analysis forcing all variables in the model was performed. I wonder
whether results would change if a more objective analysis, based on
a stepwise approach, would have been performed.
Authors’ response: we wanted to keep all the variables in the model
not only the STATISTICALLY significant ones. That is why, we have
done the regression with all the variables. And if we had taken the
stepwise approach, the final model would anyway be the same as
ours.
I do not agree with the reply. Statistics is useful to support results
and helps making clinical hypotheses. I consider important showing
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results also for the stepwise approach, given the fact that, as the
authors say: “…if we had taken the stepwise approach, the final
model would anyway be the same as ours.”
2. Original reviewer’s remark: Table 1. A column with summary data
for the whole population would be helpful. Other remarks:
Discussion. Maybe authors can compare the absolute prevalence of
Mets in their sample with other ethnic groups in the US (e.g.
Caucasian, Hispanic, etc.). This would be helpful for the reader.
Authors’ response: Instead of a simple descriptive table, we wanted
to present the characteristics by gender and show if they differed by
using a t test or a chi square test. Significant p values in most of the
cases justify our presentation manner.
We are assuming the reviewer here means overall prevalence (not
sex stratified) of MetS by absolute prevalence. We however, have
not estimated that as we wanted to present the characteristics of our
sample by gender and show how they differe
I am confused. Is the main aim of this paper to address prevalence
of Mets and its associated factors in AA or to compare Mets
prevalence in male and females AAs? The authors must clearly
indicate their objective and then present data accordingly.
VERSION 2 – AUTHOR RESPONSE
Reviewer: 1
Reviewer Name Roy T. Sabo
Institution and Country Virginia Commonwealth University
Please state any competing interests or state ‘None declared’: None declared
Please leave your comments for the authors below
The authors have addressed my concerns
Authors’ response
Thank you
Reviewer: 2
Reviewer Name Stefano Omboni
Institution and Country Italian Institute of Telemedicine, Italy
Please state any competing interests or state ‘None declared’: None declared
Please leave your comments for the authors below
The paper has been modified according to most of my indications. However, I a couple of remarks
have not been answered appropriately. I kindly ask to clarify.
1. Original reviewer’s remark: Apparently, a logistic regression analysis forcing all variables in the
model was performed. I wonder whether results would change if a more objective analysis, based on
a stepwise approach, would have been performed.
Authors’ response: we wanted to keep all the variables in the model not only the STATISTICALLY
significant ones. That is why, we have done the regression with all the variables. And if we had taken
Downloaded from http://bmjopen.bmj.com/ on June 18, 2017 - Published by group.bmj.com
the stepwise approach, the final model would anyway be the same as ours.
I do not agree with the reply. Statistics is useful to support results and helps making clinical
hypotheses. I consider important showing results also for the stepwise approach, given the fact that,
as the authors say: “…if we had taken the stepwise approach, the final model would anyway be the
same as ours.”
Authors’ response 2
We agree with the reviewer that stepwise (forward/backward) method is sometimes used for selecting
the most significantly associated variables. It is a very useful method when we have a lot of variables
to choose from. Here, we had only ten variables and wanted to show the association of MetS with all
of them. We didn’t want to drop any of the variables and lose information. That is why we didn’t use
stepwise approach. In the final model of stepwise regression, the statistically non significant variables
are not retained. In other words, in a stepwise approach, we allow the software to decide what
variables to include/exclude. Instead, in our analysis we decided what variables to include as we
wanted to show the overall relationship with all the variables. For example, in our model, for women,
lower education was associated with MetS. For men it was not (table 3). We wanted to show explicitly
the relationship between education and Mets In men too and let our readers think about the
relationship after looking at the effect measures/Confidence intervals (even if they were not
statistically significant). Now, if we had done forward selection/backward selection, for men the
software would have deleted the effect of education on MetS. And thus, we wouldn’t had been able to
show this association. Thus, to decide which variables to include in the model by researcher provides
more information, and more freedom to readers. That is why, we didn’t use a stepwise approach.
We were partially wrong when we said that the final model would be the same. It wouldn’t be as it
would not include the statistically non significant variables. However, the conclusion will remain the
same. For better clarification, we carried out the stepwise forward for men as an example, and here
are results:
In our analysis, for men, associated factors with having MetS were older age, lower physical activity,
higher body mass index, higher homocysteine and adiponectin level (p<0.05 for all).The same
variables are retained in the final step in stepwise forward regression. The rest of the variables are
excluded. We, rather wanted to include them (Education, Smoking, alcohol consumption, CRP level
and stress level) too so that we can show the relationship with all the variables. Also, including all of
them gives a better controlling of confounding. For example, in our model, we could say after
controlling for education (even if it is not statistically significant) physical activity was related to
metabolic syndrome. But in a stepwise regression we couldn’t.
2. Original reviewer’s remark: Table 1. A column with summary data for the whole population would
be helpful. Other remarks: Discussion. Maybe authors can compare the absolute prevalence of Mets
in their sample with other ethnic groups in the US (e.g. Caucasian, Hispanic, etc.). This would be
helpful for the reader.
Authors’ response: Instead of a simple descriptive table, we wanted to present the characteristics by
gender and show if they differed by using a t test or a chi square test. Significant p values in most of
the cases justify our presentation manner.
We are assuming the reviewer here means overall prevalence (not sex stratified) of MetS by absolute
prevalence. We however, have not estimated that as we wanted to present the characteristics of our
sample by gender and show how they differe
I am confused. Is the main aim of this paper to address prevalence of Mets and its associated factors
in AA or to compare Mets prevalence in male and females AAs? The authors must clearly indicate
Downloaded from http://bmjopen.bmj.com/ on June 18, 2017 - Published by group.bmj.com
their objective and then present data accordingly.
Authors’ response 2 :
We agree here with the reviewer that a column with summary data for the whole population would be
helpful and goes well with our main objective. So we added that. As we mentioned before, we also
wanted to present the characteristics by gender and show if they differed by using a t test or a chi
square test as part of our population description.
Table 1:
Characteristics of Participants of the Jackson Heart Study by Gender (N=5227)
Totala
n=5227 Mena
n=1909 Womena
n=3318 P valueb
Age in years 54.87 (12.84) 53.93 (12.93) 55.30 (12.76) 0.0002
Education level
Less than high school 18.4. 18.73 17.88
High school/GED or some college 42.2 42.82 41.83
College/associate degree or higher 39.4 38.45 40.29 0.4094
Smoking Status
Never 67.9 56.68 74.59
Former 18.9 25.33 15.30
Current 13.2 17.99 10.11 <.0001
Alcohol drinking status
Yes 47.2 58.92 38.41
No 41.08 61.59 <.0001
Total Physical Activity Scorec 8.31 (2.61) 8.64 (2.63) 8.16 (2.58) <.0001
Global Stress Total Scored 5.14 (4.21) 4.50 (4.20) 5.52 (4.45) <.0001
Body mass index (weight in kg/height in squared meter) 31.75 (7.24) 29.83±6.14 32.86 (7.59) <.0001
High Sensitivity C-Reactive Protein in mg/dL 0.51 (0.87) 0.35 (0.96) 0.60 (0.85) <.0001
Homocysteine in umol/L 9.44 (4.68) 10.17 (3.56) 9.00 (5.20) <.0001
Adiponectin level in µg/mL 5.41 (4.16) 4.15 (3.41) 6.15 (4.57) <.0001
Abdominal obesitye 62.9 41.03 75.70 <.0001
Hypertriglyceridemia 16.5 18.39 13.23 <.0001
Low HDL-Cg 37.2 33.01 39.55 <.0001
Elevated blood Pressureh 70.3 69.62 70.58 0.4616
impaired fasting glucosei 22.4 19.64 22.45 0.0171
Metabolic syndromek 34.4 27.34 38.94 <.0001
We also want to mention that, our main objective was not to compare the associated factors for men
and women and we didn’t compare the associated factors for men and women. We simply have
presented the associated factors for men and women separately. However, we also think that to be
clearer, we can modify our objective and rewrite it as:
“Using the Jackson Heart Study (JHS) data, the objective of this cross-sectional study was to report
the prevalence, associated factors and heritability estimates of MetS and its components in AA men
and women.” (page 7)
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Prevalence, associated factors and
heritabilities of metabolic syndrome and its
individual components in African Americans:
the Jackson Heart Study
Rumana J Khan, Samson Y Gebreab, Mario Sims, Pia Riestra, Ruihua
Xu and Sharon K Davis
BMJ Open 2015 5:
doi: 10.1136/bmjopen-2015-008675
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