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Batty et al. conducted a follow-up study to know the effect of
passive smoking on subsequent mortality [1]. In men in their study, self-
reported passive smoking, not salivary cotinine, could predict mortality.
From their Tables 1 and 2, salivary cotinine level was categorized into
three groups, and self-reported passive smoking was categorized binary. I
have a query on the association between self-reported passive smokin...
Batty et al. conducted a follow-up study to know the effect of
passive smoking on subsequent mortality [1]. In men in their study, self-
reported passive smoking, not salivary cotinine, could predict mortality.
From their Tables 1 and 2, salivary cotinine level was categorized into
three groups, and self-reported passive smoking was categorized binary. I
have a query on the association between self-reported passive smoking and
salivary cotinine.
Martinez-Sanchez et al. reported that geometric mean (95% confidence
interval (CI)) of salivary cotinine in general population was 1.62 (1.41-
1.87) in 210 men and 1.34 (1.19-1.51) in 299 women, whose age ranged from
16 to 64 years. They also reported that the number of second-hand smoke
(SHS) at home was 133 among 509 non-smokers, and that at work was 153
among 378 non-smoking workers. The geometric mean (95% CI) of salivary
cotinine in subjects with SHS exposure at home was 1.57 (1.32-1.86) and
that without SHS exposure was 1.42 (1.27-1.58). In contrast, the geometric
mean (95% CI) of salivary cotinine in subjects with SHS exposure at work
was 1.44 (1.23-1.69) and that without SHS exposure was 1.42 (1.24-1.63).
From this study, information on self-reported passive smoking does not
reflect the level of salivary cotinine concentration.
Taking together, I recommend Batty et al. presenting data on the
association between self-reported passive smoking and salivary cotinine
concentration by presenting 2*3 cross tables, stratified by sex. By this
information, superiority of self-reported passive smoking on the
predictive ability against salivary cotinine concentration for mortality
would be partly clarified.
References
1 Batty GD, Gale CR, Jefferis B, et al. Passive smoking assessed by
salivary cotinine and self-report in relation to cause-specific mortality:
17-year follow-up of study participants in the UK Health and Lifestyle
Survey. J Epidemiol Community Health 2014;68:1200-3.
2 Martinez-Sanchez JM, Fu M, Perez-Rios M, et al. Comparing salivary
cotinine concentration in non-smokers from the general population and
hospitality workers in Spain. Eur J Public Health. 2009;19:662-4.
Dear Sir,
Thank you very much for your interest in our research. In our JECH paper,
we analyzed data on a broad range of pediatric diseases and found,
generally, children aged 10-14 years are more vulnerable to both hot and
cold effects, compared with children of other age groups. In the OEM
paper, we analyzed pediatric asthma data and found, specifically, children
aged 10-14 years are more sensitive to the adverse impact...
Dear Sir,
Thank you very much for your interest in our research. In our JECH paper,
we analyzed data on a broad range of pediatric diseases and found,
generally, children aged 10-14 years are more vulnerable to both hot and
cold effects, compared with children of other age groups. In the OEM
paper, we analyzed pediatric asthma data and found, specifically, children
aged 10-14 years are more sensitive to the adverse impact of cold on
asthma. We used consistent statistical approach in the two papers and have
controlled for relative humidity and air pollutants. Due to limited space,
we were not be able to present the difference between different age groups
in terms of vulnerability to temperature effects on every disease.
Best,
Zhiwei
Cohort 1: born 1970s and followed between ~15-35 years of age
Cohort 2: born 1950s and followed between ~35-55 years of age
Cohort 3: born 1930s and followed between ~55-75 years of age
This study design has serious limitations for the investigation of
cohort differences in BMI trajectories (and therefore also for the
investigation of...
Cohort 1: born 1970s and followed between ~15-35 years of age
Cohort 2: born 1950s and followed between ~35-55 years of age
Cohort 3: born 1930s and followed between ~55-75 years of age
This study design has serious limitations for the investigation of
cohort differences in BMI trajectories (and therefore also for the
investigation of cohort differences in the associations of socio-economic
position with BMI trajectory). Looking at Figure 1 - how, for example, can
you calculate cohort differences in BMI at age 45 years when only cohort 2
had data at that age? How, in fact, can you make any cohort comparison of
trajectories at ages when only one cohort had data? The mixed effects
model used in the present paper will provide estimates, but these are
based on trajectories fitted beyond the age range of the data (for at
least one cohort). The only ages were cohort differences could have
reliably been estimated are those were there is overlap (e.g., difference
in BMI at age 35 years between cohort 1 and cohort 2), and this could have
been done with cross-sectional analyses.
Failure to consider the limitations of the data has led to
potentially misleading interpretation of the results, such as "adiposity
increased most quickly with age in the youngest cohort". This is expected
given that cohort 1 was of an age where BMI is known to increase more
rapidly than later in life. The design of the study makes it impossible to
disentangle age and cohort effects (except at overlapping ages). For
example, is BMI at baseline greater in cohort 3 than in cohort 1 because
they are different cohorts (exposed to different environments) or because
they are different ages? The difference will, of course, be due to a
combination of age and cohort effects, plus any possible period effect.
Cross-cohort comparisons of trajectories are a powerful strategy, but
in nearly all instances they require the trajectories for each cohort to
span the same or similar age range.
These impressive data have been widely reported. Eating plenty of
fruit and vegetables seems to be a good idea, but I am concerned at how
the need to eat 7+ portions a day to obtain maximum benefit has been
reported. As far as I can tell, the estimates for "daily" consumption were
based on a single day. Few people eat exactly the same every day and
regression to the mean suggests that most of those who ate 7+ portions on...
These impressive data have been widely reported. Eating plenty of
fruit and vegetables seems to be a good idea, but I am concerned at how
the need to eat 7+ portions a day to obtain maximum benefit has been
reported. As far as I can tell, the estimates for "daily" consumption were
based on a single day. Few people eat exactly the same every day and
regression to the mean suggests that most of those who ate 7+ portions on
the day of the survey will not have sustained such high levels of
consumption over the 7.7 years of follow-up. While these people probably
continued to eat a lot of fruit and vegetables and gain health benefits
from doing so, isn't it misleading to extrapolate the quantity of fruit
and vegetable eaten in one day into a recommendation for regular daily
consumption?
Please see our supplementary material where you can see the questions
that were asked during the interview. You will note that survey
participants were explicitly advised not to include potatoes when
considering their answers.
Please see our supplementary material where you can see the questions
that were asked during the interview. You will note that survey
participants were explicitly advised not to include potatoes when
considering their answers.
Molter et al. reported the effects of long-term exposure to
particulate matter with aerodynamic diameter <10 micrometer (PM10) and
nitrogen dioxide (NO2) on the prevalence of asthma and wheeze within a
population-based birth cohort (1). They concluded that no significant
association between long-term exposure to PM10 and NO2 and the prevalence
of either asthma or wheeze was found. In contrast, the same authors
report...
Molter et al. reported the effects of long-term exposure to
particulate matter with aerodynamic diameter <10 micrometer (PM10) and
nitrogen dioxide (NO2) on the prevalence of asthma and wheeze within a
population-based birth cohort (1). They concluded that no significant
association between long-term exposure to PM10 and NO2 and the prevalence
of either asthma or wheeze was found. In contrast, the same authors
reported that lifetime exposure to PM10 and NO2 was associated
significantly with reductions in lung volume growth by using the same
cohort (2).
On this point, Gehring et al. conducted meta-analysis with random-
effect model on the effects of air pollution on lung function in children
(3). They concluded that that current levels of NO2, total nitrogen
oxides, and particulate matter with aerodynamic diameter <2.5
micrometer (PM2.5) were significantly associated with the change in forced
expiratory volume in 1 second (FEV1), but PM10 showed no significance. As
the level of statistical significance in studies by Molter et al. or
Gehring et al. was not highly enough, final conclusion cannot be
determined. Relating to these studies, Urman et al. reported health survey
to assess the effects of near-roadway air pollution (NRAP) and regional
pollution on childhood lung function (4). They concluded that the
contribution of regional pollution to adverse lung function, evaluated by
FEV1 and forced vital capacity (FVC), was relatively larger than that of
NRAP, and NO2 contributed little to the decrease in FEV1 and FVC than
other air pollution indicators such as PM2.5 and PM10.
I have some concerns on the study outcomes. First, physiological lung
functions and subjective respiratory complains for dependent variables
would sometimes lead to the different study outcome, and both dependent
factors should be evaluated to know the adverse effect of air pollution on
respiratory organs. As one of the co-authors, I conducted questionnaire
survey for 16,663 pairs of junior high school students and their mothers
in Indonesian cities to measure the effect of air pollution on respiratory
health (5). Nine communities were set and there were inter-class and intra
-class variation of NO2. As a main result, the prevalence rates of the
symptoms of cough, phlegm, persistent cough, wheezing without a cold, and
asthma of the student were significantly correlated with the NO2 emitted
along large roads near their residences.
Second, the superiority of PM2.5 compared with PM10 could not be
confirmed, and the best aerodynamic diameter of particulate matter as an
air pollution indicator should be specified by further studies.
Finally, I recommend for considering indoor air pollution especially
by smoking (6). Anyway, cause-effect relationship would be clarified by
epidemiological cohort studies.
References
1 Molter A, Agius R, de Vocht F, et al. Effects of long-term exposure
to PM10 and NO2 on asthma and wheeze in a prospective birth cohort. J
Epidemiol Community Health 2014;68:21-8.
2 Molter A, Agius RM, de Vocht F, et al. Long-term exposure to PM10
and NO2 in association with lung volume and airway resistance in the MAAS
birth cohort. Environ Health Perspect 2013;121:1232-8.
3 Gehring U, Gruzieva O, Agius RM, et al. Air Pollution Exposure and
Lung Function in Children: The ESCAPE Project. Environ Health Perspect
2013;121:1357-64.
4 Urman R, McConnell R, Islam T, et al. Associations of children's
lung function with ambient air pollution: joint effects of regional and
near-roadway pollutants. Thorax 2013 Nov 19. doi: 10.1136/thoraxjnl-2012-
203159.
5 Duki MI, Sudarmadi S, Suzuki S, et al. Effect of air pollution on
respiratory health in Indonesia and its economic cost. Arch Environ Health
2003;58:135-43.
6 Guerra S, Stern DA, Zhou M, et al. Combined effects of parental and
active smoking on early lung function deficits: a prospective study from
birth to age 26 years. Thorax 2013;68:1021-8.
I may have missed it, but Oyebode et al. do not seem to say exactly
what they mean by a vegetable or what the exact question was. This is
important, because they do refer to a UK Department of Health website,
which states that potatoes, yams, plantain, and casava should not be
included the 5-a-day count, but sweetcorn should. I thought that
sweetcorn was a grain and so would not count it as a vegetable, though I
may b...
I may have missed it, but Oyebode et al. do not seem to say exactly
what they mean by a vegetable or what the exact question was. This is
important, because they do refer to a UK Department of Health website,
which states that potatoes, yams, plantain, and casava should not be
included the 5-a-day count, but sweetcorn should. I thought that
sweetcorn was a grain and so would not count it as a vegetable, though I
may be wrong, but if asked how many portions of vegetables I ate yesterday
would definitely have included potatoes, a staple food in the UK, if I had
eaten them. I think that the authors should clarify this.
Sir, the recent report on "extreme temperatures and paediatric
emergency" is very interesting
[1]. Xu et al. concluded that "children are at particular risk of a
variety of diseases which
might be triggered by extremely high temperatures [1]."Xu et al. also
mentioned for the effect
of climate change. In fact, Xu et al. reported a highly similar
publication in Occup Environ
Med and also noted for the effect of climate chan...
Sir, the recent report on "extreme temperatures and paediatric
emergency" is very interesting
[1]. Xu et al. concluded that "children are at particular risk of a
variety of diseases which
might be triggered by extremely high temperatures [1]."Xu et al. also
mentioned for the effect
of climate change. In fact, Xu et al. reported a highly similar
publication in Occup Environ
Med and also noted for the effect of climate change on childhood illness
with special focus
on asthma [2]. The two works should share the same groups of patients but
the conclusion is
different. In the present report, Xu et al. make a conclusion that
"children aged 10-14 years
were more sensitive to both hot and cold effects [1]" whereas they
proposed that "children
aged 10-14 years were most vulnerable to cold effects [2]." This implies
that there are many
bias in both reports. Hence, it cannot conclude on any effects from hot
and cold temperature
on pediatric illness. In addition, not only temperature but also other
climatic factors can affect
the disease incidence. The good example is the effect of humidity [3],
pollutants [3] and
ozone levels [4].
References
1. Xu Z, Hu W, Su H, Turner LR, Ye X, Wang J, Tong S. Extreme
temperatures and
paediatric emergency department admissions. J Epidemiol Community Health.
2013
Nov 23. doi: 10.1136/jech-2013-202725. [Epub ahead of print]
2. Xu Z, Huang C, Hu W, Turner LR, Su H, Tong S. Extreme temperatures and
emergency department admissions for childhood asthma in Brisbane,
Australia.
Occup Environ Med. 2013 Oct;70(10):730-5.
3. Vandini S, Corvaglia L, Alessandroni R, Aquilano G, Marsico C, Spinelli
M, Lanari
M, Faldella G. Respiratory syncytial virus infection in infants and
correlation with
meteorological factors and air pollutants. Ital J Pediatr. 2013 Jan
11;39(1):1.
4. Jones GN, Sletten C, Mandry C, Brantley PJ. Ozone level effect on
respiratory illness:
an investigation of emergency department visits. South Med J. 1995
Oct;88(10):1049-
56.
Dear Editor,
The published paper by Paananen et al, entitled "Social determinants of
mental health: a Finnish nationwide follow up study on mental disorders"1
was an interesting and rigorous study. Through a longitudinal approach,
all Finnish children who were born in a certain year (1987) were followed
through adolescence in order to examine the development of mental
disorders and assess potential SDH-related risk fact...
Dear Editor,
The published paper by Paananen et al, entitled "Social determinants of
mental health: a Finnish nationwide follow up study on mental disorders"1
was an interesting and rigorous study. Through a longitudinal approach,
all Finnish children who were born in a certain year (1987) were followed
through adolescence in order to examine the development of mental
disorders and assess potential SDH-related risk factors. For this purpose,
the authors created six multivariate models between different groups of
variables and the outcome. In addition, a full model was developed to
include the variables which showed significant associations with the
outcome in at least one of these six models. In Table 2 of that paper, the
determinants of mental disorders according to various models were
demonstrated. Nevertheless, it was not clear for us why parent's highest
educational level, parent's highest SES, parental social assistance,
cohort member's education and cohort member's received social assistance
which showed association with the outcome in models 2, 3 or 5, were not
included in the full model. At the first look, one might speculate that
these variables were included in the full model, but were not shown in
Table 2; as they might not have proved significant. But, this might not be
the correct justification as some non-significant variables e.g. "mother's
age (<20)" and "single mothers" could be found in the full model within
the same table without being significant in the full model. It would be
very kind of the authors to respond to this question and explain whether
it would be a concern in the main findings of the full model or not.
Sincerely Yours,
* Narjes Hazar, MD, Resident in Community Medicine, Department of
Community Medicine, Tehran University of Medical Sciences, Tehran, Iran
* Mojgan Karbakhsh, MD, Associate Professor in Community Medicine,
Department of Community Medicine, Tehran University of Medical Sciences,
Tehran, Iran
Reference:
1. Paananen R, Ristikari T, Merikukka M, Gissler M. Social determinants of
mental health: a Finnish nationwide follow-up study on mental disorders. J
Epidemiol Community Health. 2013 Aug 1. doi:10.1136/jech-2013-202768
________________________________________________________________________
Corresponding author:
Dr Narjes Hazar, MD, Resident in Community Medicine, Department of
Community Medicine, Tehran University of Medical Sciences, Tehran, Iran
Address: Department of Community Medicine, School of Medicine, Tehran
University of Medical Sciences, PoorSina St, Qods St, Enqelab Av, Tehran,
Iran
Email: n-hazar@razi.tums.ac.ir
Tel/Fax: +9821 88962357
This is a great contribution to the literature on fuel poverty, cold
housing, and health.
The authors call for a review of qualitative and intervention
research
related to this topic. It may be useful for readers to be made aware of
a recently updated version of a systematic review of the health and
socio-economic impacts of housing improvement published by the Campbell
and Cochrane Collaborations 1. In this revi...
This is a great contribution to the literature on fuel poverty, cold
housing, and health.
The authors call for a review of qualitative and intervention
research
related to this topic. It may be useful for readers to be made aware of
a recently updated version of a systematic review of the health and
socio-economic impacts of housing improvement published by the Campbell
and Cochrane Collaborations 1. In this review we looked at physical
improvements to housing infrastructure and this included a group of 15
quantitative (including five RCTs) and seven qualitative studies of
warmth & energy efficiency improvements. We did not include studies
which only looked at financial help with fuel bills, for example the
winter fuel allowance distributed to the elderly in the UK.
1. Thomson H, Thomas S, Sellstrom E, Petticrew M. Housing
improvements
for health and associated socio-economic outcomes. Cochrane Database of
Systematic Reviews 2013;2:Art. No.: CD008657 DOI:
10.1002/14651858.CD008657.pub2.
http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD008657.pub2/pdf/standard
Batty et al. conducted a follow-up study to know the effect of passive smoking on subsequent mortality [1]. In men in their study, self- reported passive smoking, not salivary cotinine, could predict mortality. From their Tables 1 and 2, salivary cotinine level was categorized into three groups, and self-reported passive smoking was categorized binary. I have a query on the association between self-reported passive smokin...
Dear Sir, Thank you very much for your interest in our research. In our JECH paper, we analyzed data on a broad range of pediatric diseases and found, generally, children aged 10-14 years are more vulnerable to both hot and cold effects, compared with children of other age groups. In the OEM paper, we analyzed pediatric asthma data and found, specifically, children aged 10-14 years are more sensitive to the adverse impact...
The three cohorts in this study were as follows:
Cohort 1: born 1970s and followed between ~15-35 years of age
Cohort 2: born 1950s and followed between ~35-55 years of age
Cohort 3: born 1930s and followed between ~55-75 years of age
This study design has serious limitations for the investigation of cohort differences in BMI trajectories (and therefore also for the investigation of...
These impressive data have been widely reported. Eating plenty of fruit and vegetables seems to be a good idea, but I am concerned at how the need to eat 7+ portions a day to obtain maximum benefit has been reported. As far as I can tell, the estimates for "daily" consumption were based on a single day. Few people eat exactly the same every day and regression to the mean suggests that most of those who ate 7+ portions on...
Dear Prof. Bland,
Please see our supplementary material where you can see the questions that were asked during the interview. You will note that survey participants were explicitly advised not to include potatoes when considering their answers.
http://jech.bmj.com/content/suppl/2014/03/04/jech-2013- 203500.DC1/jech-2013-203500supp1.pdf
Conflict of Interest:
N...
Molter et al. reported the effects of long-term exposure to particulate matter with aerodynamic diameter <10 micrometer (PM10) and nitrogen dioxide (NO2) on the prevalence of asthma and wheeze within a population-based birth cohort (1). They concluded that no significant association between long-term exposure to PM10 and NO2 and the prevalence of either asthma or wheeze was found. In contrast, the same authors report...
I may have missed it, but Oyebode et al. do not seem to say exactly what they mean by a vegetable or what the exact question was. This is important, because they do refer to a UK Department of Health website, which states that potatoes, yams, plantain, and casava should not be included the 5-a-day count, but sweetcorn should. I thought that sweetcorn was a grain and so would not count it as a vegetable, though I may b...
Sir, the recent report on "extreme temperatures and paediatric emergency" is very interesting [1]. Xu et al. concluded that "children are at particular risk of a variety of diseases which might be triggered by extremely high temperatures [1]."Xu et al. also mentioned for the effect of climate change. In fact, Xu et al. reported a highly similar publication in Occup Environ Med and also noted for the effect of climate chan...
Dear Editor, The published paper by Paananen et al, entitled "Social determinants of mental health: a Finnish nationwide follow up study on mental disorders"1 was an interesting and rigorous study. Through a longitudinal approach, all Finnish children who were born in a certain year (1987) were followed through adolescence in order to examine the development of mental disorders and assess potential SDH-related risk fact...
This is a great contribution to the literature on fuel poverty, cold housing, and health.
The authors call for a review of qualitative and intervention research related to this topic. It may be useful for readers to be made aware of a recently updated version of a systematic review of the health and socio-economic impacts of housing improvement published by the Campbell and Cochrane Collaborations 1. In this revi...
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