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PEER REVIEW HISTORY
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are provided with free text boxes to elaborate on their assessment. These free text comments are
reproduced below. Some articles will have been accepted based in part or entirely on reviews
undertaken for other BMJ Group journals. These will be reproduced where possible.
ARTICLE DETAILS
TITLE (PROVISIONAL)
AUTHORS
Predictors of injury mortality: findings from a large national cohort in
Thailand
Yiengprugsawan, Vasoontara; Berecki-Gisolf, Janneke; Bain,
Christopher; McClure, Roderick; Seubsman, Sam-ang; Sleigh,
Adrian
VERSION 1 - REVIEW
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Guoqing Hu
Central South University, China
01-Mar-2014
This paper reported some interesting predictors of injury mortality
based on a national cohort. The information is valuable for injury
prevention of Thailand. However, I am not sure whether these
findings could add to injury prevention knowledge. Please see
specific comments below.
1. The selection bias of study subjects should be seriously revisited
since they were recruited from distance-learning students. From age
distribution in Table 1, we could easily find the sample doesn‟t looks
representative. If this true, the data should be analyzed by including
the weight.
2. The introduction did not present a specific research question. I
cannot read any research assumptions on any predictors of injury
mortality although the authors aimed to explore the predictors.
Especially, I did not read any justification for the selection of
predictors like connected to depression. The current version did not
clearly describe the potential contribution to injury prevention
knowledge.
3. Clear research questions always determine the sample size of
cohort. However, I did not read this information and am not sure
whether the sample is sufficient to detect the relationship of potential
predictors and injury deaths.
4. The quality of national death records may affect the determination
of whether a student lived or died when the follow-up ended since
the authors using matching the baseline database and national
death record.
5. It is hard for me to understand the selection of smoking as a
potential predictor. Is there any underlying mechanism affecting the
relationship?
6. The limitation should include the potential influence of selection
bias.
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7. The grading of social and health attributes should be given clearly
definitions.
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Etienne Pracht
University of South Florida, USA
10-Mar-2014
I marked "no" concerning research ethics given the presence of a
Citizen's ID. The authors should address briefly how the data is
being safeguarded or if this is even a concern in Thailand.
Trivial:
In results section, change “history of drink driving” to “history of
drunk driving” or “history of drinking and driving.”
On page 3, under “Key Messages” change “drink driving” to “drunk
driving” or “drinking and driving.” (same on page 6, 2nd paragraph;
page 7, 1st paragraph, page 8, 1st and 2nd paragraph; page 9 2nd
paragraph)
On page 4, 1st paragraph, remove “of” before “50 million.”
On page 5, 1st paragraph: use of the first person “we” is
unconventional. Consider rewriting the sentence and removing the
first person reference.
On page 9, 2nd paragraph, change “Our study also … support to be
predictor of on-transport injury …” to “Our study also … support to
be predictive of on-transport injury …”
Suggestions:
Particularly for transport related mortality, use CID10 codes to
classify types of injury, for example traumatic brain injury (TBI), skull
and spinal cord injury (SSCI) other than TBI, fractures other than TBI
or SSCI, injuries to the thorax, and vascular injuries. This will provide
more insight concerning the mechanism and causes of injury and
may be useful for policy purposes. High rates of TBI and SSCI for
example may link directly to inadequate use of seatbelts or helmets
in case of motor cycles.
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Torsten Eken, MD PhD, senior researcher / consultant
anaesthesiologist
Dept. of Anaesthesiology
Oslo University Hospital, Ullevål
Oslo
Norway
12-Mar-2014
This manuscript is a prospective study from Thailand derived from a
research cohort of 87,037 distance-learning students, aiming to
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identify predictors for injury mortality during the first five years after
baseline. The data are highly interesting, especially because they
are collected from a large and geographically dispersed population
in a middle-income Southeast Asian country which conceivably has
other challenges and risk factors than high-income Western
countries, where most such studies have been undertaken. It will be
even more interesting to follow future studies with longer observation
times of the same cohort.
General comment:
Language in the manuscript is of somewhat variable quality, see e.g.
Introduction (“an estimated of 50 million”; mixed past and present
tense), Methods (“doctored diagnosed diseases”; “analysis of deaths
into the future”), and Table 2 (category “Not usually drive”, category
group “Number of injury”). The manuscript would benefit from a
thorough revision by a native English speaker.
Specific comments:
The “Article summary” section (Page 3) should be prepared
according to Instructions for authors, with the heading 'Strengths
and limitations of this study' and up to five bullet points that relate
specifically to the study reported.
The manuscript would benefit from explicitly reporting according to
the STROBE Statement. In particular, bias and missing data do not
seem to be addressed in sufficient detail. What was the response
rate for the initial questionnaire?
The Results section suffers from a high degree of repetition of data
already presented in the tables (e.g. Page 8, lines 7-20).
In Results, first paragraph (Page 6, lines 52-54), it is stated that
about half of the cohort members at baseline were less than 30
years old. According to Table 1, this age group constitutes less than
a third of the cohort. In the same sentence it is stated that 30% lived
in Bangkok, while Table 1 shows this fraction to be less than 18%.
Categories and groups in Table 2 and Table 4 are labelled
differently. This should be avoided. In particular, it is confusing when
“Social support” with “no” as reference category actually means
“Low social support” (Table 4). Additionally, only one of the terms
“geo-demographic” (text and Table 2) and “demo-geographic” (Table
4) should be used in the manuscript.
In the first Discussion paragraph (Page 8, lines 45-47), the
percentages of transport and non-transport injury deaths (41% and
59%) should not be rounded to only one significant digit.
Analysis results should not be introduced for the first time in
Discussion and without showing data (Page 9, lines 11-15; Page 9,
lines 30-31), neither should these undocumented results be included
as a key message (Page 3, lines 19-20).
Avoid the use of “social support” as a synonym for “low social
support” (Page 9, line 26; cf. above comment regarding Table 4).
The number of participants in the cohort is impressive, but the
question whether the cohort is representative for the general
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population is not sufficiently addressed (Page 9, lines 41-46).
VERSION 1 – AUTHOR RESPONSE
REVIEWER: Guoqing Hu
Institution and Country: Central South University, China
1. The selection bias of study subjects should be seriously revisited since they were recruited from
distance-learning students. From age distribution in Table 1, we could easily find the sample doesn‟t
looks representative. If this true, the data should be analyzed by including the weight.
>>>>>>
Thank you for your comments. The aim of the study is to investigate
predictors of injury mortality as part of the Thai Cohort Study. We
agree that the cohort is younger than the Thai population; but we
note that our cohort was not designed to measure relative
prevalence. Indeed, the utility of prospective longitudinal cohort
studies derives from the robust estimates produced for relative risks.
These relative risk estimates are based on incidence and do not
change if the cohort is reweighted (to simulate the population)
provided the weighting variables (such as age and sex) are included
in the multivariable model estimating the relative risks (Mealing et al
2010 BMC Medical Research Methodology (biomedcentral.com/14712288/10/26/)
For our analyses, we included the weighting variables as confounders
in the final model. It is worth noting other epidemiological literature
(Miettinen OS: Theoretical epidemiology principles of occurrence
research in medicine. New York: Wiley; 1985) dealing with cohorts
designed to estimate relative risks are not usually weighted to the
source population. The validity of the relative risk measured is
inherent in cohort design in both theory and practice and we would be
reluctant to depart from this standard practice.
>>>>>>
2. The introduction did not present a specific research question. I cannot read any research
assumptions on any predictors of injury mortality although the authors aimed to explore the predictors.
Especially, I did not read any justification for the selection of predictors like connected to depression.
The current version did not clearly describe the potential contribution to injury prevention knowledge.
>>>>>>
We have revised the last paragraph of the Introduction section as
follows: "Informed by our earlier research on injury morbidity, and by
related published information, this study investigated injury in more
depth using mortality as the outcome. Our study linked cohort
outcomes (survival, non-injury death, injury death) to an array of
exposures recorded at baseline including geo-demographic attributes,
social covariates, health and psychological states, and health-risk
behaviours. This analysis is both prospective and cohort-based and fills
an important gap regarding our knowledge of injury risks as an
emerging public health problem in a middle-income Asian country
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going through the health-risk transition."
>>>>>>
3. Clear research questions always determine the sample size of cohort. However, I did not read this
information and am not sure whether the sample is sufficient to detect the relationship of potential
predictors and injury deaths.
>>>>>>
Overall, the cohort was designed to answer many public health
questions in transitional Thailand and at the start we were aware of the
utility of large cohorts. Examples include the US Nurses Health Study,
UK BioBank, Million Women Study, and Australian 45 and Up. With the
baseline sample (n=87037), our cohort is large enough to detect quite
small relative effects. Indeed, we note that after five years we were
already able to detect as significant Adjusted Odds Ratio as modest as
1.4 (please see results in Table 4 of the revised manuscript).
>>>>>>
4. The quality of national death records may affect the determination of whether a student lived or
died when the follow-up ended since the authors using matching the baseline database and national
death record.
>>>>>>
The Thai death data now have almost complete coverage so almost all
deaths will be detected through this national mortality database. We
have included additional information in the Methods section as follows:
"The completeness of death registration in Thailand was 86% from
1950-2000 (ref 10), but over the last decade coverage improved to
95% (ref 23)."
>>>>>>
5. It is hard for me to understand the selection of smoking as a potential predictor. Is there any
underlying mechanism affecting the relationship?
>>>>>>
We have now explained such relationships based on previous literature
under Exposures and Confounders in the Methods section: "Health-risk
behaviours included smoking and alcohol which were shown to be
independently associated with injury risk"(refs 26-27)
As well as in the 2nd paragraph in the Discussion sections as follows:
"Effect of smoking on injury was also shown in other studies after
controlling for covariates including alcohol. Plausible explanations
include accidental fire hazard and distraction or inattention for road
traffic hazards." (ref 26-27)
>>>>>>
6. The limitation should include the potential influence of selection bias.
Downloaded from http://bmjopen.bmj.com/ on March 5, 2016 - Published by group.bmj.com
>>>>>>
We have investigated our cohort for selection bias for a variety of
scenarios and have not found any systematic link between
missingness and morbidity outcomes of interest. For mortality
analysis, by definition we follow-up the entire cohort because the data
on deaths come from a different source which is virtually 100%
complete (ie no missing data). So we are confident that the issue of
missing specific data when modelling will not affect the results and
from our earlier analyses will all be occurring at random. We have
included additional information in the Methods section under Data
processing and statistical analysis as follows: "Individuals with
missing data for given analyses were excluded (<5%), so totals vary
slightly according to available information."
And under limitation of Discussion: "We also noted that a few (<5%)
cohort members were „missing‟ data for variables used in various
models but this problem was not numerically significant."
>>>>>>
7. The grading of social and health attributes should be given clearly definitions.
We have now expanded the Methods section, including more
definitions under Exposures and confounders in the Methods section.
-----------------------------------------------------------REVIEWER: Etienne Pracht
Institution and Country: University of South Florida, USA
Given the presence of a Citizen's ID. The authors should address briefly how the data is being
safeguarded or if this is even a concern in Thailand.
>>>>>>
Thank you for your comments, confidentiality is a concern in Thailand and Australia and was
addressed in the ethical approval. We have now included additional information in the second
paragraph of the Methods section as follows:
…These confidential ID numbers were safeguarded and stored at STOU in a secure office on the
main campus with 24-hour guards on patrol. The working files of these data were de-identified and no
individual information will be released or displayed in any format.
>>>>>>
Trivial:
In results section, change “history of drink driving” to “history of drunk driving” or “history of drinking
and driving.” On page 3, under “Key Messages” change “drink driving” to “drunk driving” or “drinking
and driving.” (same on page 6, 2nd paragraph; page 7, 1st paragraph, page 8, 1st and 2nd
paragraph; page 9 2nd paragraph)
>>>>>>
Downloaded from http://bmjopen.bmj.com/ on March 5, 2016 - Published by group.bmj.com
We prefer to use our own „idiolect‟ and that means „drink driving‟. If the reviewer has a strong view
against this, we will change this in the next revision.
>>>>>>
On page 4, 1st paragraph, remove “of” before “50 million.”
>>>>>>
Revised.
>>>>>>
On page 5, 1st paragraph: use of the first person “we” is unconventional. Consider rewriting the
sentence and removing the first person reference.
>>>>>>
Revised.
>>>>>>
On page 9, 2nd paragraph, change “Our study also … support to be predictor of on-transport injury
…” to “Our study also … support to be predictive of on-transport injury …”
>>>>>>
Revised.
>>>>>>
Suggestions:
Particularly for transport related mortality, use CID10 codes to classify types of injury, for example
traumatic brain injury (TBI), skull and spinal cord injury (SSCI) other than TBI, fractures other than TBI
or SSCI, injuries to the thorax, and vascular injuries. This will provide more insight concerning the
mechanism and causes of injury and may be useful for policy purposes. High rates of TBI and SSCI
for example may link directly to inadequate use of seatbelts or helmets in case of motor cycles.
>>>>>>
We agree with your suggestions. In view of 5-year injury mortality (n=204) examined here it was not
statistically possible at this stage to investigate specific details of injury deaths. Our current data do
not contain deaths from traumatic brain injury or skull and spinal cord injury. However, given a longer
period of follow-up (feasible with Citizen ID-matched death records) allowing for sufficient injury
deaths, it will be possible to investigate such injury mechanisms in the future.
>>>>>>
-----------------------------------------------------------REVIEWER: Torsten Eken
Institution and Country: Oslo University Hospital, Ullevål, Norway
Language in the manuscript is of somewhat variable quality, see e.g. Introduction (“an estimated of 50
million”; mixed past and present tense), Methods (“analysis of deaths into the future”), and Table 2
(category “Not usually drive”, category group “Number of injury”). The manuscript would benefit from a
thorough revision by a native English speaker.
Downloaded from http://bmjopen.bmj.com/ on March 5, 2016 - Published by group.bmj.com
>>>>>>
Thank you for your comments, we have sought assistance from a
native English speaker to review and edit our draft manuscript.
>>>>>>
Specific comments:
The “Article summary” section (Page 3) should be prepared according to Instructions for authors, with
the heading 'Strengths and limitations of this study' and up to five bullet points that relate specifically
to the study reported.
>>>>>>
We have now revised the Article summary according to Instruction for
authors.
>>>>>>
The manuscript would benefit from explicitly reporting according to the STROBE Statement. In
particular, bias and missing data do not seem to be addressed in sufficient detail. What was the
response rate for the initial questionnaire?
>>>>>>
We have revisited the STROBE Statement and have added information on bias and missing data in
the Methods and Discussion sections as well as response rate for the initial questionnaire as
suggested.
>>>>>>
The Results section suffers from a high degree of repetition of data already presented in the tables
(e.g. Page 8, lines 7-20).
>>>>>>
Comments noted and have now shortened this section to highlight the key findings.
>>>>>>
In Results, first paragraph (Page 6, lines 52-54), it is stated that about half of the cohort members at
baseline were less than 30 years old. According to Table 1, this age group constitutes less than a
third of the cohort. In the same sentence it is stated that 30% lived in Bangkok, while Table 1 shows
this fraction to be less than 18%.
>>>>>>
Thank you for pointing these out, we have amended these sections.
>>>>>>
Categories and groups in Table 2 and Table 4 are labelled differently. This should be avoided. In
particular, it is confusing when “Social support” with “no” as reference category actually means “Low
social support” (Table 4). Additionally, only one of the terms “geo-demographic” (text and Table 2)
and “demo-geographic” (Table 4) should be used in the manuscript.
>>>>>>
Downloaded from http://bmjopen.bmj.com/ on March 5, 2016 - Published by group.bmj.com
We have corrected the social capital variables and also changed to „geo-demographic‟ in the
manuscript.
>>>>>>
In the first Discussion paragraph (Page 8, lines 45-47), the percentages of transport and nontransport injury deaths (41% and 59%) should not be rounded to only one significant digit.
>>>>>>
We have rewordedthis section to: ..some 40% of those were from transport and nearly 60% were nontransport injuries.
>>>>>>
Analysis results should not be introduced for the first time in Discussion and without showing data
(Page 9, lines 11-15; Page 9, lines 30-31), neither should these undocumented results be included as
a key message (Page 3, lines 19-20).
>>>>>>
We have now moved this section as additional information in Results. We also have removed this
information from Key Message section.
>>>>>>
Avoid the use of “social support” as a synonym for “low social support” (Page 9, line 26; cf. above
comment regarding Table 4).
>>>>>>
Thank you, we have clarified this.
>>>>>>
The number of participants in the cohort is impressive, but the question whether the cohort is
representative for the general population is not sufficiently addressed (Page 9, lines 41-46).
>>>>>>
We have now expanded this section as suggested.
>>>>>>
VERSION 2 – REVIEW
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Torsten Eken
Oslo University Hospital Ullevål, Norway
05-May-2014
The manuscript has improved substantially, and I have only a small
number of minor comments:
- The “Article summary” section (Page 3) still contains three
headings and eight bullet points. This section should be prepared
according to Instructions for authors: One single heading 'Strengths
and limitations of this study' followed by up to five bullet points in
total.
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- Methods, Page 6, Line 32: "70001" should probably be "7001".
- Results, Page 8, Line 34: Having low social support does not have
a statistically significant association with injury mortality (Table 4:
AOR 1.29 [0.58-2.84]).
- Table 4, Page 17, Line 48: "084" should probably be "0.84".
VERSION 2 – AUTHOR RESPONSE
Reviewer (Dr. Torsten Eken),
Thank you very much for re-reviewing manuscript. With apologies for the inconvenience with our
marked copy, in this revision we have used track changes documenting changes as well as deletions.
We also note your suggestion for future manuscripts.
We have also addressed four additional comments as follows:
- The “Article summary” section (Page 3) still contains three headings and eight bullet points. This
section should be prepared according to Instructions for authors: One single heading 'Strengths and
limitations of this study' followed by up to five bullet points in total.
We have now revised this section under 'Strengths and limitations of
this study' with four points.
- Methods, Page 6, Line 32: "70001" should probably be "7001".
We have corrected this.
- Results, Page 8, Line 34: Having low social support does not have a statistically significant
association with injury mortality (Table 4: AOR 1.29 [0.58-2.84]).
Thank you, we have amended this.
- Table 4, Page 17, Line 48: "084" should probably be "0.84".
Corrected.
We have also made some small changes in the manuscript (eg deletions of abbreviation which was
not subsequently referred to).
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Predictors of injury mortality: findings from a
large national cohort in Thailand
Vasoontara Yiengprugsawan, Janneke Berecki-Gisolf, Christopher Bain,
Roderick McClure, Sam-ang Seubsman and Adrian C Sleigh
BMJ Open 2014 4:
doi: 10.1136/bmjopen-2013-004668
Updated information and services can be found at:
http://bmjopen.bmj.com/content/4/6/e004668
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Miscellaneous
Correction
Yiengprugsawan V, Berecki-Gisolf J, Bain C, et al. Predictors of injury mortality: findings from
a large national cohort in Thailand. BMJ Open 2014;4:e004668. There was an error introduced into table 1 during the production process. The subheading ‘Divorced/Widowed’
should have been included. In addition, there were errors in the formatting. The corrected
table is below.
Table 1 Distribution of mortality by baseline social and geodemographic attributes, Thai Cohort Study
Incidence/10 000
person-years
Vital status by attributes, per cent
Cohort attributes
Injury deaths
(204)
Injury deaths (204)
Transport Non-transport
(84)
(120)
Transport
(84)
Non-transport
(120)
27.7
29.5
25.8
17.0
27.9
59.3
9.3
3.4
20.2
69.1
6.0
4.8
25.7
51.4
17.1
5.7
6
12
5
19
15
14
13
14
65.6
73.7
69.4
76.7
15
23
50.1
41.9
8.0
35.0
60.1
4.9
30.9
64.3
4.8
37.7
57.1
5.0
8
11
11
14
14
16
14.9
22.4
16.6
28.7
17.4
14.6
33.2
23.6
20.6
8.0
11.9
39.3
26.2
16.7
6.0
16.5
28.7
21.7
23.5
9.6
10
13
11
7
6
20
13
13
13
12
30.7
18.7
22.7
21.6
12.3
24.9
10.7
21.0
23.4
20.6
23.8
9.4
23.5
25.9
16.7
24.2
11.7
19.2
21.7
23.3
8
5
13
12
12
11
9
15
14
25
42.3
25.0
6.9
22.3
46.6
16.7
4.4
16.7
38.1
28.6
7.1
22.6
52.5
30.8
2.5
12.5
8
9
16
11
17
13
8
9
Alive
Other deaths
(86 457) (376)
Age groups in years
18–29
31.4
30–39
53.6
40–49
12.5
≥50
2.4
Sex
Males
45.2
Marital status
Married
38.8
Not married
56.8
Divorced/widowed
4.4
Personal monthly income
≤3000 Baht
11.0
3001–7000
30.9
7001–10 000
23.3
10 001–20 000
24.2
>20 000
10.5
Regions
Central/east
30.7
Bangkok
17.2
North
18.2
Northeast
20.9
South
13.0
Lifecourse residence
Rural–rural
43.3
Rural–urban
31.5
Urban–rural
4.2
Urban–urban
19.7
BMJ Open 2014;4:e004668corr1. doi:10.1136/bmjopen-2013-004668corr1
BMJ Open 2014;4:e004668corr1. doi:10.1136/bmjopen-2013-004668corr1
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