Oksuzyan et al. report an association between race/ethnicity and two
subtypes of childhood leukemia: acute lymphoblastic leukaemia (ALL) and
acute myeloid leukaemia (AML).1 Accordingly, the researchers suggest that
there are genetic, cultural, and environmental factors involved in the
etiology of childhood leukaemia [1].
Importantly, Oksuzyan et al. made a significant effort to examine and
control for the poten...
Oksuzyan et al. report an association between race/ethnicity and two
subtypes of childhood leukemia: acute lymphoblastic leukaemia (ALL) and
acute myeloid leukaemia (AML).1 Accordingly, the researchers suggest that
there are genetic, cultural, and environmental factors involved in the
etiology of childhood leukaemia [1].
Importantly, Oksuzyan et al. made a significant effort to examine and
control for the potential role of socioeconomic status (SES) on this
association. In particular, the authors used paternal education levels
used as a proxy for SES given that a significant percentage of information
on maternal education was missing from the birth registry used [1]. This
strategy faces several challenges given the complex association of race,
education, and SES.
The use of paternal education might not appropriately account for the
adverse health effects which might result (at least in part) from residing
in single-parent homes. It has been widely documented that children
frequently exhibit poor health outcomes in single-parent homes due to
causal chain of effects related to parent's education, SES, and income
[2]. Moreover, the information regarding paternal education as a proxy for
SES was obtained from the California Birth Registry [1]. It is possible
that this data does not adequately represent the SES of the cases used in
the study given that the father identified might not have provided
financial support for the child.
In addition, the use of parental education as a proxy for SES may not
be an appropriate method as average income frequently varies in jobs
requiring similar education levels [3]. It is possible that these
variations occur more frequently among different ethnic/racial groups;
potentially as a result of systemic prejudice and/or unequal employment
opportunities [3].
Oksuzyan et al. report an association between race/ethnicity and
childhood leukaemia [1]. Due to potential challenges in using paternal
education as a proxy for SES, the inclusion of maternal education and a
discussion regarding SES in single-parent homes would have been valuable.
References
1 Oksuzyan S, Crespi CM, Cockburn M, Mezei G, Vergara X, Kheifets L.
Race/ethnicity and the risk of childhood leukaemia: A case-control study
in California. J Epidemiol Community Health Published Online First: 19
March 2015. doi:10.1136/jech-2014-204975
2 Gucciardi E, Celasun N, Stewart DE. Single-mother families in
Canada. Can J Public Health 2004;95(1):70-73.
3 Williams DR. Race, socioeconomic status, and health. The added
effects of racism and discrimination. Ann N Y Acad Sci 1999;896:173-188.
Lauderdale et al. examined the association between perceived
fair/poor health and sleep duration by several methods [1]. The authors
concluded that U-shaped relationship between sleep duration and prevalence
of fair/poor health was observed only with measuring sleep with survey
sleep hours and survey calculated sleep time. In contrast, there was no
association between long sleep duration and increased prevalence of
fair/...
Lauderdale et al. examined the association between perceived
fair/poor health and sleep duration by several methods [1]. The authors
concluded that U-shaped relationship between sleep duration and prevalence
of fair/poor health was observed only with measuring sleep with survey
sleep hours and survey calculated sleep time. In contrast, there was no
association between long sleep duration and increased prevalence of
fair/poor health by actigraphy. However, I am not fully convinced by their
arguments.
First, the authors well understand the limitation of actigraphy,
named Actiwatch Spectrum, for sleep evaluation and the need of validation
study of actigraphy against sleep polysomnography. There is a difference
between brain activity and physical movement during sleep, and the
discrepancy of sleep parameters between polysomnography and actigraphy is
obvious for insomniacs [2]. When calculating total sleep time by
actigraphy, the authors selected default sleep/awake sensitivity setting
(40 counts per minutes), and also carried out a sensitivity analysis with
a lower threshold of 20. Although the correlation coefficient between
sleep duration with different threshold setting was greater than 0.99,
actual sleep duration differs 18 minute in an average. Kushida et al.
reported the best sleep/awake threshold of Actiwatch for detecting
wakefulness as "high-sensitivity" setting (20 counts per minutes) [3].
Peterson et al. adopted default sleep/awake sensitivity setting of
Actiwatch, and described the overestimation of total sleep time and
underestimation of wake-after sleep onset [4]. These reports present that
level of sleep/awake threshold is important for estimating sleep duration
by actigraphy.
Second, the numbers of subjects in each category of sleep duration
seems useful information in their study. The authors described the mean
value of sleep duration by survey sleep hours and by actigraph total sleep
time were 7.5 hours and 7.2 hours, but the prevalence of fair/poor health
in subjects with sleep duration >9 hours by survey sleep hours was two-
fold higher than that by actigraph total sleep time. The correlation
coefficient between sleep duration by survey sleep hours and by actigraph
total sleep time was 0.29, and I suspect that some subjects with long
sleep duration by actigraphy do not actually keep enough sleep duration.
Anyway, sleep polysomnography study is required to confirm the lack
of U-shaped association between sleep duration and prevalence of fair/poor
health.
References
1 Lauderdale DS, Chen JH, Kurina LM, et al. Sleep duration and health
among older adults: associations vary by how sleep is measured. J
Epidemiol Community Health 2015 Nov 3. doi: 10.1136/jech-2015-206109
2 Natale V, Leger D, Martoni M, et al. The role of actigraphy in the
assessment of primary insomnia: a retrospective study. Sleep Med
2014;15:111-5.
3 Kushida CA, Chang A, Gadkary C, et al. Comparison of actigraphic,
polysomnographic, and subjective assessment of sleep parameters in sleep-
disordered patients. Sleep Med 2001;2:389-96.
4 Peterson BT, Chiao P, Pickering E, et al. Comparison of actigraphy
and polysomnography to assess effects of zolpidem in a clinical research
unit. Sleep Med 2012;13:419-24.
Dear editor,
We have read with great interest the meta-analysis submitted by Li and colleagues1, which investigated the association between fish consumption and depression risk. We warmly and greatly congratulate and applaud for their important work. However, an issue existed in this study should be noted.
These authors stated that observational study including cross-sectional, case-control, and cohort study was eligible for their...
Dear editor,
We have read with great interest the meta-analysis submitted by Li and colleagues1, which investigated the association between fish consumption and depression risk. We warmly and greatly congratulate and applaud for their important work. However, an issue existed in this study should be noted.
These authors stated that observational study including cross-sectional, case-control, and cohort study was eligible for their inclusion criteria in inclusion criteria subsection. However, the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA)2 was used to guide reporting their meta-analysis. Important is that the PRISMA is designed to use mainly in systematic review and meta-analysis with randomized controlled trials (RCTs) rather than meta-analysis with observational studies in epidemiology. Controversially, the Meta-analysis of Observational Studies in Epidemiology (MOOSE)3 is developed for reporting this given meta-analysis. And thus, the authors should adopted the MOOSE to guide reporting their meta-analysis on this given topic preferably we suggested in order to further improve reporting quality.
1. Li F, Liu X, Zhang D. Fish consumption and risk of depression: a meta-analysis. J Epidemiol Community Health 2015; doi: 10.1136/jech-2015-206278.
2. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meya-analyses: the PRISMA statement. J Clin Epidemiol 2009; 62:1006-1012.
3. Stroup DF, Berlin JA, Moton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000; 283:2008-2012.
Hintsa et al. examined the effect of effort, reward and job control
on the exit from the labour market by a 6-year follow-up study in workers
at the age of 61 years or younger [1]. The author adopted binary logistic
regression analysis by adjusting several variables, and concluded that
effort-reward imbalance (ERI), effort and job control were significant
predictors for exit from the labour market. In contrast, reward wa...
Hintsa et al. examined the effect of effort, reward and job control
on the exit from the labour market by a 6-year follow-up study in workers
at the age of 61 years or younger [1]. The author adopted binary logistic
regression analysis by adjusting several variables, and concluded that
effort-reward imbalance (ERI), effort and job control were significant
predictors for exit from the labour market. In contrast, reward was not
selected as a significant predictor. I have some concerns on their study.
First, the authors did not use effort, reward and job control
simultaneously as independent variables for predicting exit from the
labour market. Schmidt et al. recently reported that the sum score of
effort significantly increased and the sum score of reward significantly
decreased as ERI increased in 4141 samples in Germany [2]. If
multicollinearity among independent variables cannot be solved, the
simultaneous use of ERI, effort and reward should be handled with caution,
because ERI was simply calculated as the logarithmic value of [(sum score
of effort)*7]/[(sum score of reward)*3]. But inset of effort and reward
simultaneously as independent variables into logistic model seems
appropriate, because the authors measured stressful psychological work
environment by ERI model, and each factor has a different dimension for
psychometry. In addition, simultaneous use of job control from another
theoretical stress model should also be considered in combination with ERI
model after evaluating multicollinearity.
Second, statistical results differed by different combination of
adjusting variables in their study. The adjusting variables were selected
to know the net association between exit from the labour market and
effort, reward or job control, and I recommend selecting full-adjudging
model in their study. If discrepancies of statistical results by selecting
different combination of adjusting variable exist, stability of
significance cannot be guaranteed in the statistical model.
Finally, there are other reasons of exit from the labour market than
the causes of working environment. On this point, explanation rate of exit
from the labour market by factors form ERI model and job control should be
presented. The authors selected workers at the age of 61 years or younger,
and cause of exit by family support is suspected especially in women. This
would partly be related to the sex differences in the average age of
withdrawal from the labour market. Anyway, further study is commended to
confirm the causal association.
References
1 Hintsa T, Kouvonen A, McCann M, et al. Higher effort-reward
imbalance and lower job control predict exit from the labour market at the
age of 61 years or younger: evidence from the English Longitudinal Study
of Ageing. J Epidemiol Community Health 2015;69:543-9.
2 Schmidt B, Bosch JA, Jarczok MN, et al. Effort-reward imbalance is
associated with the metabolic syndrome - findings from the Mannheim
Industrial Cohort Study (MICS). Int J Cardiol 2015;178:24-8.
Xu et al report an association between deranged liver enzymes e.g. alanine transaminase (ALT) in Chinese people residing in Southern China and the incidence of diabetes [1].
The authors examined multiple potential confounding factors which could influence liver enzymes e.g. alcohol consumption & adiposity.
However, although the authors briefly mentioned chronic viral hepatitis infections i.e. chronic hepatitis B...
Xu et al report an association between deranged liver enzymes e.g. alanine transaminase (ALT) in Chinese people residing in Southern China and the incidence of diabetes [1].
The authors examined multiple potential confounding factors which could influence liver enzymes e.g. alcohol consumption & adiposity.
However, although the authors briefly mentioned chronic viral hepatitis infections i.e. chronic hepatitis B virus (HBV) & hepatitis C virus (HCV), I think they did not give this confounder sufficient weight and did not report HBV/HCV prevalence data in the cohort studied. This is a significant shortcoming of this study.
As the authors acknowledged, chronic HBV & HCV are relatively common in China, with the prevalence of chronic HBV of 11.3% for males, 8.2% for females & for chronic HCV 3.1% for males, 3.3% for females [2].
Therefore, as these are common infections in China, the underlying population prevalence of chronic HBV & HCV infection in the study cohort could account for at least some of the deranged liver enzymes in the study population. Unfortunately, the lack of data on these infections prevents quantitative analysis of the effect these hepatitides may have on the liver enzyme profiles in this cohort.
The authors acknowledged a possible association between HCV and diabetes, but there is also emerging evidence that chronic HBV infection is associated with insulin resistance [3]. Furthermore, chronic HBV complicated by cirrhosis may be associated with diabetes mellitus [4]. The apparent association between deranged liver enzymes and the development of diabetes may not be due to hepatitis/transaminitis per se, but may reflect underlying specific pathologies such as chronic HBV and HCV.
The high prevalence of chronic HBV and HCV in the Chinese population and the associations of these infections with insulin resistance & diabetes mellitus means that the authors' conclusions underplay the possible contribution of chronic viral hepatitis to the development of diabetes. Thus, the conclusions should perhaps have included recommendations that patients with deranged liver enzymes should be screened for these viral hepatitis infections, so that they can be considered for antiviral treatment which would be beneficial not just in terms of future diabetes risk, but also the well-known risks of cirrhosis & hepatocellular carcinoma in these patients.
References:
1. Xu L, Jian CQ, Schooling CM et al. Liver enzymes and incident diabetes in China: a prospective analysis of 10764 participants in the Guangzhou Biobank Cohort Study. J Epidemiol Community Health 2015;69:1040-1044
2. Huang H, Hu XF, Zhao FH et al. Estimation of cancer burden attributable to infection in Asia. J Epidemiol 2015 doi:10.2188/jea.JE20140215
3. Lee JG, Lee S, Kim YJ et al. Association of chronic viral hepatitis B with insulin resistance. World J Gastro 2012;18(42):6120-6126
4. Zhang J, Shen Y, Cai H et al. Hepatitis B virus infection status and risk of type 2 diabetes mellitus: A meta-analysis. Hepatol Res 2015 doi:10.1111.hepr.12481
Oksuzyan et al. report an association between race/ethnicity and two
subtypes of childhood leukemia: acute lymphoblastic leukaemia (ALL) and
acute myeloid leukaemia (AML).1 Accordingly, the researchers suggest that
there are genetic, cultural, and environmental factors involved in the
etiology of childhood leukaemia [1].
Importantly, Oksuzyan et al. made a significant effort to examine and
control for the poten...
Oksuzyan et al. report an association between race/ethnicity and two
subtypes of childhood leukemia: acute lymphoblastic leukaemia (ALL) and
acute myeloid leukaemia (AML).1 Accordingly, the researchers suggest that
there are genetic, cultural, and environmental factors involved in the
etiology of childhood leukaemia [1].
Importantly, Oksuzyan et al. made a significant effort to examine and
control for the potential role of socioeconomic status (SES) on this
association. In particular, the authors used paternal education levels
used as a proxy for SES given that a significant percentage of information
on maternal education was missing from the birth registry used [1]. This
strategy faces several challenges given the complex association of race,
education, and SES.
The use of paternal education might not appropriately account for the
adverse health effects which might result (at least in part) from residing
in single-parent homes. It has been widely documented that children
frequently exhibit poor health outcomes in single-parent homes due to
causal chain of effects related to parent's education, SES, and income
[2]. Moreover, the information regarding paternal education as a proxy for
SES was obtained from the California Birth Registry [1]. It is possible
that this data does not adequately represent the SES of the cases used in
the study given that the father identified might not have provided
financial support for the child.
In addition, the use of parental education as a proxy for SES may not
be an appropriate method as average income frequently varies in jobs
requiring similar education levels [3]. It is possible that these
variations occur more frequently among different ethnic/racial groups;
potentially as a result of systemic prejudice and/or unequal employment
opportunities [3].
Oksuzyan et al. report an association between race/ethnicity and
childhood leukaemia [1]. Due to potential challenges in using paternal
education as a proxy for SES, the inclusion of maternal education and a
discussion regarding SES in single-parent homes would have been valuable.
References
1 Oksuzyan S, Crespi CM, Cockburn M, Mezei G, Vergara X, Kheifets L.
Race/ethnicity and the risk of childhood leukaemia: A case-control study
in California. J Epidemiol Community Health Published Online First: 19
March 2015. doi:10.1136/jech-2014-204975
2 Gucciardi E, Celasun N, Stewart DE. Single-mother families in
Canada. Can J Public Health 2004;95(1):70-73.
3 Williams DR. Race, socioeconomic status, and health. The added
effects of racism and discrimination. Ann N Y Acad Sci 1999;896:173-188.
The author commented on the paucity of research on the point where
physical exercise in polluted air becomes more harmful than beneficial. I
would like to share our research findings conducted more than 10 years ago
in Hong Kong (Yu et al, 2004). We compared the physical fitness of school
children who regularly performed physical exercise with those who did not.
In a less polluted district (annual mean P...
The author commented on the paucity of research on the point where
physical exercise in polluted air becomes more harmful than beneficial. I
would like to share our research findings conducted more than 10 years ago
in Hong Kong (Yu et al, 2004). We compared the physical fitness of school
children who regularly performed physical exercise with those who did not.
In a less polluted district (annual mean PM10=44.9 ug/m3), children who
regularly did physical exercise had significantly better cardiopulmonary
fitness (with a higher predicted maximum oxygen update of 1.8 mL/Kg/min
among children who did regular exercise). By contrast, among children in a
'high pollution district' (PM10=57.6 ug/m3), there was no significant
difference in their cardiopulmonary fitness whether they exercised
regularly or not (the difference in VO2 max between children with regular
physical exercise and those without was insignificant, at 0.6 mL/Kg/min).
The concentration of PM10 in mainland Chinese cities are much higher than
our 'high pollution district', and outdoor physical exercise may be more
harmful than beneficial.
Tze Wai Wong
Reference: Yu ITS, Wong TW, Liu HJ. Impact of air pollution on
cardiopulmonary fitness of schoolchildren. Journal of Occupational and
Environmental Medicine 2004; 46:946-954.
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.
Oksuzyan et al. report an association between race/ethnicity and two subtypes of childhood leukemia: acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML).1 Accordingly, the researchers suggest that there are genetic, cultural, and environmental factors involved in the etiology of childhood leukaemia [1].
Importantly, Oksuzyan et al. made a significant effort to examine and control for the poten...
Lauderdale et al. examined the association between perceived fair/poor health and sleep duration by several methods [1]. The authors concluded that U-shaped relationship between sleep duration and prevalence of fair/poor health was observed only with measuring sleep with survey sleep hours and survey calculated sleep time. In contrast, there was no association between long sleep duration and increased prevalence of fair/...
Hintsa et al. examined the effect of effort, reward and job control on the exit from the labour market by a 6-year follow-up study in workers at the age of 61 years or younger [1]. The author adopted binary logistic regression analysis by adjusting several variables, and concluded that effort-reward imbalance (ERI), effort and job control were significant predictors for exit from the labour market. In contrast, reward wa...
Xu et al report an association between deranged liver enzymes e.g. alanine transaminase (ALT) in Chinese people residing in Southern China and the incidence of diabetes [1].
The authors examined multiple potential confounding factors which could influence liver enzymes e.g. alcohol consumption & adiposity. However, although the authors briefly mentioned chronic viral hepatitis infections i.e. chronic hepatitis B...
Oksuzyan et al. report an association between race/ethnicity and two subtypes of childhood leukemia: acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML).1 Accordingly, the researchers suggest that there are genetic, cultural, and environmental factors involved in the etiology of childhood leukaemia [1].
Importantly, Oksuzyan et al. made a significant effort to examine and control for the poten...
Dear sir
The author commented on the paucity of research on the point where physical exercise in polluted air becomes more harmful than beneficial. I would like to share our research findings conducted more than 10 years ago in Hong Kong (Yu et al, 2004). We compared the physical fitness of school children who regularly performed physical exercise with those who did not. In a less polluted district (annual mean P...
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...
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