Reviewer's report
Title:Helicobacter pylori in apparently healthy children aged 0-12 years in urban
Kampala, Uganda: a community-based cross sectional survey.
Version: 1Date:22 February 2010
Reviewer: Vincent Plagnol
Reviewer's report:
From a statistical point of view, the work presented by Hestvik and colleagues is
relatively simple (which is in no way a flaw) but some points are unclear and
require clarification.
Firstly, I am not sure why the authors show unadjusted ORs. I would only show
the adjusted ones which are more informative. But is is essential that table 1
includes P-values.
Page 11: "Excluding the `sharing a toilet` only marginally altered ... in the final
model"
What final model are the authors talking about? And I am not sure this is relevant
here anyway, the point of the paper is not model selection. And why would this
association be spurious? Because P-values are not shown it is difficult to assess
the meaning of this finding from Table 1. It is really essential to show these
P-values and discuss why the association would be spurious, if it is indeed.
Surprising results can be the most interesting ones so I would suggest further
exploration of this question.
Page 12: I read "We found an increasing prevalence in the age groups". It should
probably be something like: "We found an increased prevalence in the older aged
groups"?
I am not sure the use of a principal component analysis for the wealth index is
very helpful. If it is important it would be nice to show how the two most
significant covariates contribute to this separation in three groups (maybe a
scatter plot showing asset and income on each axis and a color coding for the
three categories?). I also do not understand what the authors mean when they
say that the model captured 82% of the results, or that the first PCA captured
31.3% of the variance. Variance of what variable? I would much rather see a
simplified version of this graph based on 1-2 covariates of interest, combined
with a graphical display to make sure that the separation makes sense. The
statistics in this paper are not reassuring enough to fully trust the PCA without
some intuitive data visualization.
Last paragraph of the results: "change the findings in the final analysis". Is this
paper not already providing the final analysis? This paragraph is oddly written. If
HIV positive children are excluded this is fine, and the authors should say this
rather than do some imprecise hand waving. If the authors have not done a
proper comparison, they should probably not mention it and only describe the
exclusion criteria, how many children were excluded, and the motivations behind
this exclusion.
There are a few typos on page 4: "suchas" missing a space, "recent,ly" has a
misplaced comma. Authors use "human beings" quite often, simply "humans"
would do the job just as well I think.
Lastly, figure 1 is not essential and should be removed. The data shown in the
figure can be included in Table 1 instead.
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Needs some language corrections before being
published
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
I declare that I have no competing interest.
Reviewer's report
Title:Helicobacter pylori in apparently healthy children aged 0-12 years in urban
Kampala, Uganda: a community-based cross sectional survey.
Version: 1Date:22 February 2010
Reviewer: Vincent Plagnol
Reviewer's report:
From a statistical point of view, the work presented by Hestvik and colleagues is
relatively simple (which is in no way a flaw) but some points are unclear and
require clarification.
Firstly, I am not sure why the authors show unadjusted ORs. I would only show
the adjusted ones which are more informative. But is is essential that table 1
includes P-values.
Page 11: "Excluding the `sharing a toilet` only marginally altered ... in the final
model"
What final model are the authors talking about? And I am not sure this is relevant
here anyway, the point of the paper is not model selection. And why would this
association be spurious? Because P-values are not shown it is difficult to assess
the meaning of this finding from Table 1. It is really essential to show these
P-values and discuss why the association would be spurious, if it is indeed.
Surprising results can be the most interesting ones so I would suggest further
exploration of this question.
Page 12: I read "We found an increasing prevalence in the age groups". It should
probably be something like: "We found an increased prevalence in the older aged
groups"?
I am not sure the use of a principal component analysis for the wealth index is
very helpful. If it is important it would be nice to show how the two most
significant covariates contribute to this separation in three groups (maybe a
scatter plot showing asset and income on each axis and a color coding for the
three categories?). I also do not understand what the authors mean when they
say that the model captured 82% of the results, or that the first PCA captured
31.3% of the variance. Variance of what variable? I would much rather see a
simplified version of this graph based on 1-2 covariates of interest, combined
with a graphical display to make sure that the separation makes sense. The
statistics in this paper are not reassuring enough to fully trust the PCA without
some intuitive data visualization.
Last paragraph of the results: "change the findings in the final analysis". Is this
paper not already providing the final analysis? This paragraph is oddly written. If
HIV positive children are excluded this is fine, and the authors should say this
rather than do some imprecise hand waving. If the authors have not done a
proper comparison, they should probably not mention it and only describe the
exclusion criteria, how many children were excluded, and the motivations behind
this exclusion.
There are a few typos on page 4: "suchas" missing a space, "recent,ly" has a
misplaced comma. Authors use "human beings" quite often, simply "humans"
would do the job just as well I think.
Lastly, figure 1 is not essential and should be removed. The data shown in the
figure can be included in Table 1 instead.
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Needs some language corrections before being
published
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
I declare that I have no competing interest.
Please review this paper.
user
Reviewer's report
Title:Helicobacter pylori in apparently healthy children aged 0-12 years in urban
Kampala, Uganda: a community-based cross sectional survey.
Version: 1Date:22 February 2010
Reviewer: Vincent Plagnol
Reviewer's report:
From a statistical point of view, the work presented by Hestvik and colleagues is
relatively simple (which is in no way a flaw) but some points are unclear and
require clarification.
Firstly, I am not sure why the authors show unadjusted ORs. I would only show
the adjusted ones which are more informative. But is is essential that table 1
includes P-values.
Page 11: "Excluding the `sharing a toilet` only marginally altered ... in the final
model"
What final model are the authors talking about? And I am not sure this is relevant
here anyway, the point of the paper is not model selection. And why would this
association be spurious? Because P-values are not shown it is difficult to assess
the meaning of this finding from Table 1. It is really essential to show these
P-values and discuss why the association would be spurious, if it is indeed.
Surprising results can be the most interesting ones so I would suggest further
exploration of this question.
Page 12: I read "We found an increasing prevalence in the age groups". It should
probably be something like: "We found an increased prevalence in the older aged
groups"?
I am not sure the use of a principal component analysis for the wealth index is
very helpful. If it is important it would be nice to show how the two most
significant covariates contribute to this separation in three groups (maybe a
scatter plot showing asset and income on each axis and a color coding for the
three categories?). I also do not understand what the authors mean when they
say that the model captured 82% of the results, or that the first PCA captured
31.3% of the variance. Variance of what variable? I would much rather see a
simplified version of this graph based on 1-2 covariates of interest, combined
with a graphical display to make sure that the separation makes sense. The
statistics in this paper are not reassuring enough to fully trust the PCA without
some intuitive data visualization.
Last paragraph of the results: "change the findings in the final analysis". Is this
paper not already providing the final analysis? This paragraph is oddly written. If
HIV positive children are excluded this is fine, and the authors should say this
rather than do some imprecise hand waving. If the authors have not done a
proper comparison, they should probably not mention it and only describe the
exclusion criteria, how many children were excluded, and the motivations behind
this exclusion.
There are a few typos on page 4: "suchas" missing a space, "recent,ly" has a
misplaced comma. Authors use "human beings" quite often, simply "humans"
would do the job just as well I think.
Lastly, figure 1 is not essential and should be removed. The data shown in the
figure can be included in Table 1 instead.
Level of interest: An article whose findings are important to those with closely
related research interests
Quality of written English: Needs some language corrections before being
published
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
I declare that I have no competing interest.
assistant