The article by Mohindra SK et al brings about clearly the effect of
caste and socioeconomic position on women’s health [1]. If this is the case
in Kerala, which is one of the states with good health indicators in
India, one can imagine what it would be with more poorer and deprived
states in India. We believe that along with socioeconomic status and
caste, female literacy is one of the key determinant...
The article by Mohindra SK et al brings about clearly the effect of
caste and socioeconomic position on women’s health [1]. If this is the case
in Kerala, which is one of the states with good health indicators in
India, one can imagine what it would be with more poorer and deprived
states in India. We believe that along with socioeconomic status and
caste, female literacy is one of the key determinants of women's health in
general and Sexual and Reproductive Health in particular. In order to
demonstrate this and add more to what has been highlighted in the article
we present data from select Indian states.
The table compares the literacy rates, contraceptive use and birth
order of 3 or more, in eight states of India. The states are grouped into
two categories based on the literacy status. One can observe that as the
literacy status improves so would the contraceptive use and as a
consequence of that the birth order would decrease (Table 1). Lack of
education can have detrimental effects to change in demographics as well.
For example, it has been observed in India that the literacy rate among
Hindus is 65.1% while that among Muslims is 59.1% and one can draw a
relationship of this to the fact that growth rate of Hindus have decreased
from 23.7% in 1961-71 to 20.3% in 1991-2001, whereas that for the Muslims
have increased from 30.8% to 36.0% during the same period. [2]
We believe that it is important to empower women with education to
help them make healthier choices about their health.
References
1. Mohindra S K, Haddad S and Narayana D. Women’s health in a rural
community in Kerala, India: do caste and socioeconomic position matter.
Journal of Epidemiology and Community Health. Dec 2006; 60;19:1020-1025
2. Census of India. available at
http://www.censusindia.net/religiondata/statement.pdf (accessed on 05-12-
2006)
3. Census of India. available at
http://www.censusindia.net/t_00_006.html (accessed on
05-12-2006)
4. Reproductive and Child Health. Summary Report-INDIA. 2002-2004.
available at http://www.rchindia.org/sr/chep5.pdf (accessed on 05-12-2006)
Well researched and well written paper, indeed.
We japanese as a whole don't even know what is going to happen.
Only the powerful Ministry of Finance and Japan Tobacco Co know
what is going on. I hope everybody in Japan read this article.
By doing so, their way of people manipulation will slowly change.
Thank you for your in depth research work.
Although there is nothing incorrect in the effort by Karpati et al. [1]
to appraise changing neighborhood mortality inequalities in New York City,
the effort is compromised by a failure to recognize the statistical
tendency whereby the rarer an outcome, the greater the relative difference
in experiencing it (and the smaller the relative difference in avoiding
it). The authors point out that relative i...
Although there is nothing incorrect in the effort by Karpati et al. [1]
to appraise changing neighborhood mortality inequalities in New York City,
the effort is compromised by a failure to recognize the statistical
tendency whereby the rarer an outcome, the greater the relative difference
in experiencing it (and the smaller the relative difference in avoiding
it). The authors point out that relative inequalities in mortality in the
United Kingdom have been increasing despite absolute improvements in life
expectancy at all levels. But in times of declining mortality one should
expect to observe increasing relative differences in mortality rates
between more and less advantaged groups solely as a result of the
mortality decline [2-6]. Whether there occurred in the United Kingdom any
change in relative health that was not solely a result of declining
mortality has gone unexamined [6]. In the case of New York City, the fact
that overall declines in mortality resulted in even a small reduction in
relative mortality differences, rather than the increase in relative
differences that would more typically occur, should be interpreted
(although cautiously [2,6]) as a favorable development.
The patterns in Table 1 of the Karpati article regarding changes in
relative differences in death rates from particular diseases must be
similarly interpreted in light of the tendency for declines in prevalences
to increase relative differences and increases in prevalence to reduce
relative differences. But it remains difficult to draw conclusions about
meaningful changes in relative differences regarding particular causes –
i.e., changes that are not solely a consequence of changes in prevalence – with any degree of confidence [2,6].
The tendency for relative differences to be greatest where an outcome
is rarest also suggests that certain of the study’s broader findings
concerning relative differences in adverse health outcomes across New York
City neighborhoods are pretty much what one should expect. The study
found that relative differences in mortality are greater among the young
than the old. Such a pattern is what one ought to expect to find (and
what one typically in fact finds) simply because mortality is rarer among
the young [6]. Absolute mortality differences, as well as relative
differences in survival rates, however, tend to be greater among the
old [6,7]. The authors also find that while heart disease and cancer show
comparatively small age-adjusted mortality rate ratios across
neighborhoods, such diseases are among the most important contributors to
excess mortality in the poorest neighborhoods. Such a pattern is also to
be expected simply because more common outcomes tend to show small
relative differences but large absolute differences (as reflected in Table
1); and it is the absolute difference that determines the contribution of
a particular diseases to a group’s overall excess mortality (whether
measured in absolute or relative terms). One similarly observes that
nationally the causes of death with comparatively small black-white
mortality ratios tend to be the largest contributors to overall racial
disparities in mortality [8].
The authors also employ the relative index of inequality (RII) and
years of potential life lost before age 65 (YPLL-65) to appraise changes
in the size of inequalities over time. The RII, which is simply a
variation on the standard relative difference, is subject to the same
interpretive problems as the relative difference with respect to
identifying changes in the respective situation of two groups that are not
solely a consequence of changes in prevalence of an outcome. YPLL-65,
like longevity differences, would seem also to change solely as a result
of changes in the overall prevalence of mortality, but with a direction of
change that is difficult to predict [2,6]. Thus, neither of these measures
obviates the difficult problem or distinguishing changes in the relative
health of two groups that are solely a consequence of overall declines in
mortality from those that are not. The expanded monitoring of health
patterns suggested by the authors should be undertaken in conjunction with
an effort to develop tools for addressing such problem.
James P. Scanlan
References
1. Karpati AM, Bassett MT, McCord C. Neighborhood mortality
inequalities in New York City, 1989-1991 and 1999-2001. J Epidemiol
Community Health 2006;60:1060-1064.
2. Scanlan JP. Can we actually measure health disparities? Chance
2006;19(2):47-51:
http://www.jpscanlan.com/images/Can_We_Actually_Measure_Health_Disparities.pdf.
3. Scanlan JP. Measuring health disparities. J Public Health Manag
Pract 2006;12(3):294 [Lttr]:
http://www.nursingcenter.com/library/JournalArticle.asp?Article_ID=641470
(accessed Nov. 10, 2006).
4. Scanlan JP. Race and Mortality. Society 2000;37(2):19-35:
http://www.jpscanlan.com/images/Race_and_Mortality.pdf.
6. Scanlan JP. The misinterpretation of health inequalities in the
United Kingdom: Paper presented at: British Society for Population
Studies Annual Conference 2006, Southampton, England, Sept. 18-20, 2006:
http://www.jpscanlan.com/images/BSPS_2006_Complete_Paper.pdf (accessed
Nov. 10, 2006).
7. Scanlan JP. Measuring health inequalities: Paper presented at:
5th International Conference on Health Economics, Management and Policy,
Athens, Greece, June 5-7, 2006:
http://www.jpscanlan.com/images/Measuring_Health_Inequalities.pdf.
8. Wong MD, Shapiro MF, Boscardin WJ, Ettner SL. Contributions of
major diseases to disparities in mortality. N Engl J Med. 2002;347:1585 -
92.
Does the article "Marital Status and Longevity in the United States
Population" correct for possible confounding? The subjects could have
different degrees of mental and emotional stability, leading to better or
worse lifestyle choices, risk-taking behaviour, and attention to health.
Maybe people who are more sedate, emotionally stable, successful, avoid
drugs and heavy use of alcohol, etc. are more l...
Does the article "Marital Status and Longevity in the United States
Population" correct for possible confounding? The subjects could have
different degrees of mental and emotional stability, leading to better or
worse lifestyle choices, risk-taking behaviour, and attention to health.
Maybe people who are more sedate, emotionally stable, successful, avoid
drugs and heavy use of alcohol, etc. are more likely to get married, less
likely to get divorced, and also more likely to take care of themselves,
engage in fewer dangerous hobbies, and take better care of their health.
In order to correct for such possible factors, the authors of the
study would need access to the results of psychological tests on the
subjects, and to apply sophisticated adjustments to account for
personality differences. The results of the study might not be valid
after such a heavy degree of required adjustment, even if the data were
available.
It has come to my attention that an error crept into the
description of the GAZEL cohort study in the article published by Hyde et
al. in the October 2006 issue of the Journal of Epidemiology and Community
Health.
The correct number of participants is 20 624, rather than 15 000. The
best description of the cohort's baseline characteristics is provided in
Goldberg M, Leclerc A, Bonenfant S,...
It has come to my attention that an error crept into the
description of the GAZEL cohort study in the article published by Hyde et
al. in the October 2006 issue of the Journal of Epidemiology and Community
Health.
The correct number of participants is 20 624, rather than 15 000. The
best description of the cohort's baseline characteristics is provided in
Goldberg M, Leclerc A, Bonenfant S, Chastang JF, Schmaus A, Kaniewski
N,Zins M. Cohort profile: the GAZEL Cohort Study. Int J Epidemiol. 2006 In
Press [Available online].
Medical care, [1] or medical couldn't care less? I am a mere boy of
52, but so far in my career I have never witnessed a Consultant in Public Health Medicine
set foot inside a school
or attend a parents evening
or even work alongside school nurses to train schoolteachers
undertaking compulsory Personal, Social and Health Education classes, in
relation to local population n...
Medical care, [1] or medical couldn't care less? I am a mere boy of
52, but so far in my career I have never witnessed a Consultant in Public Health Medicine
set foot inside a school
or attend a parents evening
or even work alongside school nurses to train schoolteachers
undertaking compulsory Personal, Social and Health Education classes, in
relation to local population needs.
In the past, I have observed other Physicians, and Psychiatrists,
work closely with 'special schools' for children with disabilities (whose
clientele are now dispersed over a much larger number of 'mainstream
schools'). I can think of a dwindling number of grey-haired Community
Paediatricians and Family Doctors (with the old Diploma in Child Health)
who still make heroic efforts to safeguard children from abuse, anywhere,
anytime.
The welfare and social inclusion of young people is a priority for
many members of the European Union. In England, 'Every Child Matters' and
the emerging Children's Trusts (based in Education) seek many worthwhile
outcomes under their Be Healthy standards.
Does Public Health Medicine want young 'active consumers'? [1] Bring
it on!
References
[1] Levin L, Ashton JR. The problem with school health. Journal of
Epidemiology and Community Health 2006; 60: 818.
We appreciate Huisman and Avendano’s interest in our research letter
on income inequality and the prevalence of mental illness. [1] They point
out that the correlations we report between income inequality and mental
illness are driven by the position of the United States as an outlier,
with a very high prevalence of mental illness and very high levels of
income inequality. [2]
We appreciate Huisman and Avendano’s interest in our research letter
on income inequality and the prevalence of mental illness. [1] They point
out that the correlations we report between income inequality and mental
illness are driven by the position of the United States as an outlier,
with a very high prevalence of mental illness and very high levels of
income inequality. [2]
As we pointed out in our report, our study was exploratory and
intended to stimulate further research, rather than a definitive
examination of this question. We felt it important to restrict our report
to those eight countries with strictly comparable prevalence estimates
provided by WHO. [3] However, we have also examined this relationship
including a further four countries (Canada, Australia, Singapore and the
UK) with prevalence estimates from population-based surveys of adults
(data available upon request). In these analyses the correlation between
income inequality and mental illness is r=0.63, p value=0.03, and this
correlation is unaffected by the exclusion of the USA (r=0.63, p
value=0.09). In fact, if we limit our analyses to the four English-
speaking nations for which we have data (USA, UK, Canada and Australia),
the correlation is even stronger (r=0.99, p=0.003), suggesting that within
a larger framework of nations the USA may be representative of a
particular relationship between social structure and mental health, rather
than an outlier.
So, the USA might be an outlier with respect to continental Western
Europe, and within Western Europe there may be insufficient variation in
income inequality to explore its relation to health. Nevertheless, within
a larger grouping of nations, the positive correlation of income
inequality and prevalence of mental health suggests interesting avenues
for further research. Rather than contradicting the notion that income
inequality might be an important determinant of health, these preliminary
results support our recent finding of overwhelming evidence in support of
this hypothesis among studies conducted at the level of nations. [4]
References
1.Pickett, K.E., O.W. James, and R.G. Wilkinson, Income inequality
and the prevalence of mental illness: a preliminary international
analysis. J Epidemiol Community Health, 2006. 60(7): p. 646-7.
2.Huisman, M. and M. Avendano, Income inequality and the prevalence
of mental illness: the “outlier” US drives the association. J Epidemiol
Community Health Online, 2006(26 September).
3.Demyttenaere, K., et al., Prevalence, severity, and unmet need for
treatment of mental disorders in the World Health Organization World
Mental Health Surveys. Jama, 2004. 291(21): p. 2581-90.
4.Wilkinson, R.G. and K.E. Pickett, Income inequality and population
health: A review and explanation of the evidence. Soc Sci Med, 2006.
62(7): p. 1768-84.
In their report on income inequality and the prevalence of mental
illness based on data from several European countries and the US, Pickett,
James and Wilkinson conclude that higher national levels of income
inequality are linked to higher prevalence of mental illness [1]. They
base their conclusion on an observed correlation of 0.73 between income
inequality (the ratio of the top to the bottom 20%...
In their report on income inequality and the prevalence of mental
illness based on data from several European countries and the US, Pickett,
James and Wilkinson conclude that higher national levels of income
inequality are linked to higher prevalence of mental illness [1]. They
base their conclusion on an observed correlation of 0.73 between income
inequality (the ratio of the top to the bottom 20% of the income
distribution) and the national prevalence of mental illness of these eight
countries.
We find it difficult to agree with this conclusion. The high
correlation between income inequality and the prevalence of mental illness
is clearly driven by the “outlier” US. Recalculations of the same data
(See Table 1 in their paper) indicate that leaving the US out of the
analysis results in a non-significant correlation of 0.24 of income
inequality with prevalence of any mental illness. When considering only
severe mental illness instead of any mental illness, removing the US gives
a correlation of –0.03! This clearly suggests that at least within Western
Europe, there is no association between income inequality and the
prevalence of mental illness.
What should then be the conclusion from these results? This
exploratory study does show that the US is an outlier, both in terms of
income inequality and the prevalence of mental illness. Indeed, this seems
to be in line with other findings, suggesting that the US is a ‘special
case’ with respect to the correlation of income inequality with health
[2][3]. These extreme values may point at the impact of broader healthcare
and income distribution policies in the US, which clearly contrast with
more egalitarian policies in Western European countries. Further research
on the political and macro-economic determinants of population mental
health is therefore warranted. But given that even a country with large
income inequality such as Italy can have a low prevalence of mental
illness [1], these findings suggest that the country-level determinants of
mental illness do not lie primarily with income inequality, but elsewhere.
Martijn Huisman,
Mauricio Avendano
Department of Public Health,
Erasmus MC,
University Medical Center Rotterdam,
P.O. Box 2040,
3000 CA Rotterdam,
The Netherlands
Conflict of interest: None
References
1) Pickett KE, James OW, Wilkinson RG. Income inequality and the
prevalence of mental illness: a preliminary international analysis. J
Epidemiol Community Health 2006;60:646-647.
2) Lynch J, Davey Smith G, Hillemeier M, Shaw M, Raghunathan T,
Kaplan G. Income inequality, the psychosocial environment, and health:
comparisons of wealthy nations. Lancet 2001;358:194-200.
3) Mackenbach JP. Income inequality and population health. Br Med J
2002;324:1-2.
We write to you with respect to our paper published in the Journal
about the risk of occupational injury in foreign workers in Spain. Using
the first available data in Spain on the subject, for the year 2003, the
study found that foreign workers ran risks much higher than those of
Spanish workers for both non-fatal and fatal occupational injury. The
same data have recently become available for 20...
We write to you with respect to our paper published in the Journal
about the risk of occupational injury in foreign workers in Spain. Using
the first available data in Spain on the subject, for the year 2003, the
study found that foreign workers ran risks much higher than those of
Spanish workers for both non-fatal and fatal occupational injury. The
same data have recently become available for 2004, and we would like to
briefly discuss the results, methodology used to obtain them, and some
conclusions we believe to be important to the study of health and social
issues such as these using secondary data.
Both anonymous data sets were obtained from the Ministry of Labour
and Social Issues (MTAS), which maintains a registry of fatal and non-
fatal occupational injuries in insured workers. Nationality was classified
as Missing/Unknown (000), Spanish (724), or Foreign (any other value)
according to codes employed by MTAS.
The results obtained are very clearly contradictory, showing an
increase in the number of both non-fatal and fatal injuries in Spanish
workers, and an enormous reduction in all injuries in foreign workers from
2003 to 2004. The reduction is such that for non-fatal injuries in 2004,
foreign status appears to have a slight protective influence: relative
risks (Spanish workers as reference) were 0.95 (Confidence Interval at
95%: 0.94-0.96) for non-fatal and 1.2 (0.9-1.4) for fatal. Furthermore,
there is also a sizeable reduction in the number of cases where the
nationality was missing, going from 19,689 such cases in 2003 to only
2,402 in 2004.
The data for both years are similar in many ways, such as sample size
and proportion of men and women, and were treated in the same way both
years. However, the data have one difference that is very relevant here.
In 2003, the variable nationality included codes that were “invented”;
that is, not part of the original coding scheme. As those codes neither
indicated missing data (000) nor Spanish nationality (724), we included
them as foreign workers. In 2004 there are no such erroneous codes; all
those included correspond to a country listed in the coding scheme.
Obviously, such results cast doubt on the results obtained in 2003.
We fully acknowledge that the decision to include the “invented” codes as
foreigner workers is one that can be questioned. But we also see here a
valuable opportunity to question and debate the reliability of currently
available administrative data; as we can now doubt the results obtained
from 2003, we could just as easily doubt the information from 2004. To
echo thoughts from the original study, the data we have are limited both
in scope and in quality. Though we are halfway through 2006, data from
2004 have only recently become available, and we will have to wait until
2005 data are released to truly evaluate the patterns of occupational
injury studied here.
Such doubts are extremely important in a field heavily dependent on
rigorously collected administrative data. These data are often the only
feasible way to examine broadly certain aspects of population health and
track changes over time. As public health researchers we have a
responsibility to make use of and report on the data available to us. We
also have a responsibility to acknowledge data limitations and advocate
for improvement. With migration as an ever-increasing reality, in Spain
and elsewhere, it is critical to stay abreast of the occupational health
situation of those new arrivals living and working among us. To do so, we
must have good data.
As we wait for further data, we will continue our study of immigrant
occupational health through the use of other study designs, and hope that
this issue will remain a pressing one in the public health field. Our
results put into sharp relief situations critical to the understanding of
worker health in Spain and in other European countries. Equally, they
highlight questions that remain to be answered, not the least of which is
the gaping hole in the information we have on foreign workers.
Sincerely,
Emily Q. Ahonen, MPH
Fernando G. Benavides, MD, PhD
Occupational Health Research Unit. Pompeu Fabra University (Barcelona)
References
Ahonen E, Benavides FG. Risk of fatal and non-fatal occupational
injury in foreig workers in Spain. J Epidemiol Community Health.
2006;60:424-426.
In endeavoring to understand the mechanisms underlying the greater
mortality of persons never married, Kaplan and Kronick draw inferences
from the sizes of the never married penalties in various subgroups.1 For
example, questioning whether there is a cumulative effect of years spent
unmarried, the authors note that they find a greater penalty for never
marrying among the young than the old. In ques...
In endeavoring to understand the mechanisms underlying the greater
mortality of persons never married, Kaplan and Kronick draw inferences
from the sizes of the never married penalties in various subgroups.1 For
example, questioning whether there is a cumulative effect of years spent
unmarried, the authors note that they find a greater penalty for never
marrying among the young than the old. In questioning whether it may be
poor health that leads to never marrying rather than the reverse, they
note that the penalty for never marrying is greatest among those who
report themselves to be in excellent health.
In giving interpretive weight to these comparisons of the sizes of
the penalty for never marrying, the authors overlook the tendency whereby
the rarer an outcome, the greater the relative difference in experiencing
it (though the smaller the relative difference in avoiding it). Such
tendency can be observed in virtually any data set that allows one to
examine the relationships of two groups with respect to falling above or
below various points on a continuum of factors associated with
experiencing or avoiding some outcome.2-6.
Thus, there would be a tendency for the relative difference in
mortality between the never married and the rest of the population to be
greater among the young (where mortality rates are lower) than among the
old (where mortality rates are higher) even if the risk distributions of
the never married and the remainder the population are more similar among
the young than the among the old (in consequence of the cumulative impact
of the longer term social isolation of the older never married or any
other factor). It warrants note that we also observe that relative
socioeconomic differences in mortality tend to be greater among the young
than among the old (though, as with the instant study, the absolute
differences are greater than among the old than among the young).7,8.
Similarly, the fact that mortality is lower among those in excellent
health than those in poorer health will tend to cause the never married
penalty to be greater among those in excellent health than among those in
poorer health, just as, for example, racial differences in mortality tend
to be greater among low risk than high risk groups.4
These are merely tendencies, of course. Other factors can counteract
(or enhance) the tendencies to some degree and sometimes may overwhelm
them. Note, for example, that even though mortality is lower among women
than among men, until age 65 the never married penalty is greater among
men than among women. We also observe generally that socioeconomic
differences in mortality are usually greater among women than among men.8.
Note, too, that Kaplan and Kronick’s Table 2 shows that, while the pattern
whereby the never married penalty decreases with age is present for women
as well as men, the differences are small and nonsignificant for women.
That these situations seem contrary to the described tendency does not
mean that the tendency is not operating, but merely that other factors may
be sufficient to outweigh it. In any case, the existence of the tendency
renders problematic efforts to draw inferences on the basis of the sizes
of the difference between the rates of two groups observed within
different segments of the population. Certainly it is futile to attempt
to draw such inferences without attempting to take the tendency into
account. At the same time, it is difficult to estimate the role of the
tendency given that ordinarily we cannot view the actual risk distribution
of the groups being examined.1,6.
The expectation that the sizes of differences in experiencing an
outcome will vary depending on the prevalence of an outcome does not apply
only to relative differences, but, so far as I can tell, to all measures
that are at times employed to appraise the size of differences in the
rates at which two groups experience some outcome. In that regard, it
warrants note, that while it is difficult enough to meaningfully compare
ratios of rates of experiencing an outcome given that the ratios will tend
to be larger where the outcome is rarer, such comparisons are even more
difficult in the case of odds ratios (which were used in the instant study
and which are typically used in studies of socioeconomic differences in
morbidity). For while changes in prevalence tend to cause patterns of
changes in odds ratios that are similar to the patterns observed for rate
ratios in circumstances where an outcome is sufficiently rare that odds
ratios approximate rate ratios, where the outcome is more common, patterns
of odds ratio changes do not exhibit the same consistency as patterns of
rate ratio changes. Thus, in some settings, though not necessarily the
instant one, comparisons of odds ratios can be even more problematic than
comparisons or rate ratios.1,6.
Finally, an additional difficulty with the instant study involves the
role of AIDS-related deaths. The never married penalty that warrants
study mainly involves the effects of social isolation. Gay men tend to be
disproportionately never married and to comprise a much higher proportion
of AIDS-related deaths than they comprise of the population. And AIDS
deaths comprise a substantial proportion of deaths among young men.
Arguably some AIDS deaths involve an element of risk-taking that may be an
effect of social isolation related to being unmarried. But in general
the unmarried status of gay men implicates different considerations vis-à-
vis social isolation from the unmarried status of other men. Thus, the
inclusion of the high number of AIDS-related deaths among young men
compromises the study’s ability to identify the common effects of social
isolation.
References
1. Kaplan RM, Kronick RG. Marital status and longevity in the
United States Population. J Epidemiol Community Health 2006:60:760-765.
2. Scanlan JP. Can we actually measure health disparities? Chance
2006;19(2):47-51.
3. Scanlan JP. Measuring health disparities. J Public Health Manag
Pract 2006;12(3):294 [Lttr]:
http://www.nursingcenter.com/library/JournalArticle.asp?Article_ID=641470.
4. Scanlan JP. Race and mortality. Society 2000;37(2):19-35:
http://www.jpscanlan.com/images/Race_and_Mortality.pdf.
7. Mackenbach JP, Bakker MJ, for the European Network on
Interventions and Policy to Reduce Inequalities in Health. Tackling
socioeconomic inequalities in health: analysis of European experiences.
Lancet 2003;362:1409-1414.
8. Huisman M., Kunst A.E. Bopp M., et al. Educational inequalities
in cause specific mortality in middle-aged and older men and women in
eight western European populations. Lancet 2005;36:493-500.
Dear Sir,
The article by Mohindra SK et al brings about clearly the effect of caste and socioeconomic position on women’s health [1]. If this is the case in Kerala, which is one of the states with good health indicators in India, one can imagine what it would be with more poorer and deprived states in India. We believe that along with socioeconomic status and caste, female literacy is one of the key determinant...
Dear Editor
Well researched and well written paper, indeed. We japanese as a whole don't even know what is going to happen. Only the powerful Ministry of Finance and Japan Tobacco Co know what is going on. I hope everybody in Japan read this article. By doing so, their way of people manipulation will slowly change. Thank you for your in depth research work.
Dear Editor
Although there is nothing incorrect in the effort by Karpati et al. [1] to appraise changing neighborhood mortality inequalities in New York City, the effort is compromised by a failure to recognize the statistical tendency whereby the rarer an outcome, the greater the relative difference in experiencing it (and the smaller the relative difference in avoiding it). The authors point out that relative i...
Dear Editor
Does the article "Marital Status and Longevity in the United States Population" correct for possible confounding? The subjects could have different degrees of mental and emotional stability, leading to better or worse lifestyle choices, risk-taking behaviour, and attention to health. Maybe people who are more sedate, emotionally stable, successful, avoid drugs and heavy use of alcohol, etc. are more l...
Dear Editors,
It has come to my attention that an error crept into the description of the GAZEL cohort study in the article published by Hyde et al. in the October 2006 issue of the Journal of Epidemiology and Community Health.
The correct number of participants is 20 624, rather than 15 000. The best description of the cohort's baseline characteristics is provided in Goldberg M, Leclerc A, Bonenfant S,...
Dear Editor
Medical care, [1] or medical couldn't care less? I am a mere boy of 52, but so far in my career I have never witnessed a Consultant in Public Health Medicine
set foot inside a school
or attend a parents evening
or even work alongside school nurses to train schoolteachers undertaking compulsory Personal, Social and Health Education classes, in relation to local population n...
Dear Editor
We appreciate Huisman and Avendano’s interest in our research letter on income inequality and the prevalence of mental illness. [1] They point out that the correlations we report between income inequality and mental illness are driven by the position of the United States as an outlier, with a very high prevalence of mental illness and very high levels of income inequality. [2]
As we pointed o...
Dear editor,
In their report on income inequality and the prevalence of mental illness based on data from several European countries and the US, Pickett, James and Wilkinson conclude that higher national levels of income inequality are linked to higher prevalence of mental illness [1]. They base their conclusion on an observed correlation of 0.73 between income inequality (the ratio of the top to the bottom 20%...
Dear Editor,
We write to you with respect to our paper published in the Journal about the risk of occupational injury in foreign workers in Spain. Using the first available data in Spain on the subject, for the year 2003, the study found that foreign workers ran risks much higher than those of Spanish workers for both non-fatal and fatal occupational injury. The same data have recently become available for 20...
Dear Editor,
In endeavoring to understand the mechanisms underlying the greater mortality of persons never married, Kaplan and Kronick draw inferences from the sizes of the never married penalties in various subgroups.1 For example, questioning whether there is a cumulative effect of years spent unmarried, the authors note that they find a greater penalty for never marrying among the young than the old. In ques...
Pages