We use cookies to improve our service and to tailor our content and advertising to you.More infoYou can manage your cookie settings via your browser at any time. To learn more about how we use cookies, please see our cookies policy.
In their recent paper, Smith and Katikireddi (2012) provide a useful
outline of theories for understanding policymaking. The article is aimed
at public health practitioners and researchers who are seeking to shape
policy. It rightly encourages them to draw on relevant theory to more
productively guide their interactions with, and potential influence on,
relevant policy. This is a timely and welcome...
In their recent paper, Smith and Katikireddi (2012) provide a useful
outline of theories for understanding policymaking. The article is aimed
at public health practitioners and researchers who are seeking to shape
policy. It rightly encourages them to draw on relevant theory to more
productively guide their interactions with, and potential influence on,
relevant policy. This is a timely and welcome message. However, authors
have failed to include an important shift in political science and policy
studies that is highly relevant to the process of shaping public health
policy.
Approaches to thinking about policy come from three epistemological
frameworks (Shaw 2010). Firstly, a rationalist framework that conceives of
policymaking in terms of clear 'stages' that actors simply feed evidence
into. Secondly a political rationalist framework that recognises the way
that ideas, values, interests and actors interact in a more complex, non-
linear way to shape policy. Thirdly a policy-as-discourse framework that
recognises that language and social interaction shape policy. Authors
focus briefly on the first, largely on the second and not at all on the
third. Whilst this perhaps reflects the dominance of rationalist thinking
about policy, by not acknowledging policy-as-discourse authors fail to
provide the glossary that they claim to provide.
A policy-as-discourse approach has relevance for those seeking to
shape health policy because, amongst other things, it acknowledges that
social problems are identified and addressed through the activities of
different interest groups (clinicians, managers, patients and so on). By
drawing attention to the language and arguments used by groups, such an
approach encourages public health practitioners and researchers to
consider how policy problems are framed, by who and why. It also
encourages them to consider their own language and how they might
productively use it to challenge public health policies and open up
possibilities for social change.
We encourage those interested in shaping policy to consider, not only
the theories outlined by Smith and Katikireddi, but also policy-as-
discourse. Such theory reflects a wider 'linguistic and argumentative
turn' in the social and political sciences (Fischer and Forester 1996),
which has been very influential in some areas of social policy, but has
yet to filter through into health policy. Doing so will not only provide
additional insight into what are often complex areas of policy (e.g.
health inequalities), but also ensure a more comprehensive theoretical
landscape from which public health practitioners and researchers can
select appropriately.
References
Fisher F and Forester J (1996) The Argumentative Turn in Policy
Analysis and Planning. Durham/London, Duke University Press.
Shaw SE (2010) Reaching the parts that other theories and methods
can't reach: How and why a policy-as-discourse approach can inform health-
related policy. Health 14(2) 196-212
Smith KE and Katikireddi SV (2012) A glossary of theories for
understanding policymaking. JECH Online First doi:10.1136/jech-2012-
200990.
It is with great interest we read "Frequent shopping by men and women increases survival in the older Taiwanese population" by Chang et al.1 The authors have found that highly frequent shopping compared to never or rarely is likely to predict survival as it captures several dimensions of personal well-being, health and security as well as contributing to the community's cohesiveness and economy. The significance has remained after...
It is with great interest we read "Frequent shopping by men and women increases survival in the older Taiwanese population" by Chang et al.1 The authors have found that highly frequent shopping compared to never or rarely is likely to predict survival as it captures several dimensions of personal well-being, health and security as well as contributing to the community's cohesiveness and economy. The significance has remained after adjustment for a number of covariates, including common and classical risk factors such as smoking, alcohol, and physical inactivity, in the regression models. However, the most important mortality predictor particularly in the adulthood, hypertension, was not taken into account.2
More than that, recent research have discovered that higher blood pressure in early adulthood was associated with elevated risk of all-cause mortality and other chronic diseases.3 In this context, therefore, without considering hypertension symptoms in the pathway between shopping behaviour and risk of death could seriously bias the effect that was observed since without having hypertension shall exhibit stronger protective effect on survival. In spite of this, the prevalence of hypertension is predicted to increase more among women than men.4 In the current study, women actually did less shopping than men. These together are likely to imply a correlation between hypertension and shopping behaviour on risk of death. Furthermore, as shopping is related to money status, individual income would be a potential buffer because people with more money and/or higher socioeconomic status are more capable of doing shopping. I wonder this should be also considered before drawing the conclusion and bringing the public health message to the general public.
References
1. Chang YH, Chen RCY, Wahlqvist ML, Lee MS. Frequent shopping by men and women increases survival in the older Taiwanese population. J Epidemiol Community Health. 2012;66:e20.
2. Chiang CE, Wang TD, Li YH, Lin TH, Chien KL, Yeh HI, Shyu KG, Tsai WC, Chao TH, Hwang JJ, Chiang FT, Chen JH; Hypertension Committee of the Taiwan Society of Cardiology. 2010 Guidelines of the Taiwan Society of Cardiology for the management of hypertension. J Formos Med Assoc. 2010109:740-773.
3. Gray L, Lee IM, Sesso HD, Batty GD. Blood pressure in early adulthood, hypertension in middle-age, and future cardiovascular disease mortality: HAHS (Harvard Alumni Health Study). J Am Coll Cardiol. 2011;58:2396-2403.
4. Pimenta E. Hypertension in women. Hypertens Res. 2012;35:148-152.
The aim of the authors was to assess the validity and agreement of
self-reported prevalent cases of stroke and AMI in the Spanish cohort of
the European Prospective Investigation into Cancer and Nutrition (EPIC).
They calculated sensitivity, specificity, positive predictive values and ?
statistics. The sensitivity of self-reported prevalent cases of stroke was
81.3% and that for AMI was 97.7%. The positive predictive value...
The aim of the authors was to assess the validity and agreement of
self-reported prevalent cases of stroke and AMI in the Spanish cohort of
the European Prospective Investigation into Cancer and Nutrition (EPIC).
They calculated sensitivity, specificity, positive predictive values and ?
statistics. The sensitivity of self-reported prevalent cases of stroke was
81.3% and that for AMI was 97.7%. The positive predictive value was 22.2%
and 60.7% for stroke and AMI, respectively. The agreement between self-
report questionnaire results and medical records was substantial (?=0.75)
for AMI but not for stroke (?=0.35).1
To scientifically assess the accuracy (validity) of a test, there are 7
estimations named Sensitivity, Specificity, Positive Predictive Value
(PPV), Negative Predictive Value (NPV), Likelihood ratio positive, LR+
(true positive/false positive), Likelihood ratio negative, LR- (false
negative/true negative) and finally Odds ratio, OR (true results /false
results).2 Considering limitations of the first 4 estimations, preferably
the last 3 estimations are being reported. However, due to the different
range of these estimations [(LR+ from 1 to infinity; the higher, the
better) (LR- from 0 to 1; the closer to the zero, the better) and OR
greater than 50 indicates a valid test), usually two different tests are
being evaluated compared to a gold standard. 2
Regarding agreement, to compute kappa value, just concordant cells are
being considered, whereas discordant cells should also be taking into
account in order to reach a correct estimation of agreement (Weighted
kappa).2-4
It is crucial to know that there is no value of kappa that can be regarded
universally as indication good agreement. Statistics cannot provide a
simple substitute for clinical judgment. Two important weaknesses of k
value to assess agreement of a qualitative variable are as follow: It
depends upon the prevalence in each category and also depends upon the
number of categories. So it is obvious that the less our categories, the
higher will be our kappa value which can easily lead to
misinterpretation.2-4
S.Sabour, MD, PhD
References:
1- Mach?n M, Arriola L, Larra?aga N, Amiano P, Moreno-Iribas C, Agudo A,
Ardanaz E, Barricarte A, Buckland G, Chirlaque MD, Gavrila D, Huerta JM,
Mart?nez C, Molina E, Navarro C, Quiros JR, Rodr?guez L, Sanchez MJ,
Gonz?lez CA, Dorronsoro M. Validity of self-reported prevalent cases of
stroke and acute myocardial infarction in the Spanish cohort of the EPIC
study. J Epidemiol Community Health. 2012 May 10
2- Epidemiology, biostatistics and preventive medicine, Jeckel, 1st
edition, 2008
3- Modern Epidemiology, K. Rothman, 3 rd edition, 2010
4- Clinical Epidemiology, D.E Grobbee, 1st edition, 2010
I was interested to read your letter/article in the Journal of
Epidemiology and Community Health, and your conclusion that there were
significant reductions in IMR. You wondered whether this might have been
due to interventions such as Sure Start and the Health in Pregnancy grant.
I would be surprised if the latter played any significant part, as it came
far too late in pregnancy to do anything significant and, anecdotally...
I was interested to read your letter/article in the Journal of
Epidemiology and Community Health, and your conclusion that there were
significant reductions in IMR. You wondered whether this might have been
due to interventions such as Sure Start and the Health in Pregnancy grant.
I would be surprised if the latter played any significant part, as it came
far too late in pregnancy to do anything significant and, anecdotally at
least, was often spent on items that would not contribute to health
outcomes. As a midwife and health visitor, it seemed the most ill-thought-
out piece of spending the government put in place, spending that could so
easily have been better used earlier in pregnancy, if directed more
specifically - maybe to provide maternal folic acid and Vitamin D freely
to all pregnant women.
If we are seeing an improvement in inequalities in IMR, I would
submit that higher breastfeeding initiation and continuation rates, and
the investment that the government of the time put into supporting
breastfeeding (largely withdrawn now), could well be a significant
contributing factor. Recent DH data comparing admissions and breastfeeding
rates show a significant reduction in admissions of infants to hospital
for conditions such as chest infections, bronchiolitis and gastroenteritis
in areas where breastfeeding rates are high, even where deprivation levels
are also high. Modelling by Bartick and Reinhold (2010) in the US showed
that, if 90% women followed the recommendations to breastfeeding
exclusively for 6 months, over 900 excess infant deaths would be prevented
each year, as well as $13 billion annually. I believe that similar
modelling is being undertaken in the UK, and I would imagine it might well
show similar results, even if on a smaller scale.
Conflict of Interest:
I am Infant Feeding Coordinator for a London borough, tasked with leading the borough to UNICEF Baby Friendly accreditation, to ensure that all mothers, however they choose to feed their babies, receive the information and support they need to do that appropriately and successfully.
Numerous studies conducted have found evidence for a positive
relation between green space in peoples environment and self reported
indicators of morbidity and mortality (Lee and Maheswaran, 2011). The
authors in this study have found mortality from all causes to be higher in
greener cities. Attempts have been made to adjust for factors which may
act as confounders, however other community level factors have not been
tak...
Numerous studies conducted have found evidence for a positive
relation between green space in peoples environment and self reported
indicators of morbidity and mortality (Lee and Maheswaran, 2011). The
authors in this study have found mortality from all causes to be higher in
greener cities. Attempts have been made to adjust for factors which may
act as confounders, however other community level factors have not been
taken into account which influence mortality levels like health care
access and crime rates in the cities. Part of the relation found in the
study between green space and all causes mortality may be explained by
indirect selection. Indirect selection takes place when people with
certain characteristics related to well being (such as income) tend to
live in a greener environment. Migration flows are related to
sociodemographic characteristics such as age, income and education (Maas
et al, 2009). Possible migration of the elderly post retirement to greener
areas may most likely skew all cause mortality levels and which needs
investigation. Moreover, no association was found between greenness and
mortality from diseases of lung cancer, heart disease, diabetes and motor
vehicle fatalities when analyzed individually. Analysis of the mortality
data based on the city of residence may prove more helpful in
understanding the association between greenness and health, given that
many diseases develop temporally and exposure could have occurred in the
past.
Also, the authors have used the proportion of households without an
automobile as a measure of automobile dependency for urban form and
function. The number of household members and the number of cars per
household have been ignored and which influence the measure of automobile
dependency differently.
References
1. Lee ACK and Maheswaran. The healthcare benefits of urban green spaces:
a review of the evidence. J Public Health (2011) 33 (2); 212-222
2. Maas J, Verheij RA, Spreeuwenberg P, Groenewegen PP. Physical activity
as a possible mechanism behind the relationship between green space and
health: a multilevel analysis. BMC Public Health. 2008 Jun 10;8:206.
Sir,
I read with interest the article by Yu-Hung Chang et al.(1) Authors have articulated some limitations in their paper.
However, the findings are derived from purpose of the Elderly Nutrition and Health Survey in Taiwan (1999-2000), done to assess the diet, nutrition and health of persons aged 65 and above in Taiwan. One of the common and often forgotten limitation of such surveys is Survivor Bias.(2) People who go to shoppin...
Sir,
I read with interest the article by Yu-Hung Chang et al.(1) Authors have articulated some limitations in their paper.
However, the findings are derived from purpose of the Elderly Nutrition and Health Survey in Taiwan (1999-2000), done to assess the diet, nutrition and health of persons aged 65 and above in Taiwan. One of the common and often forgotten limitation of such surveys is Survivor Bias.(2) People who go to shopping might be those who are healthy and survived minor illness. Hence, Survival is a determinant of whether people remain active and whether they can go to shopping. Also, people who are debilitated, disabled and who have severe illness might not be able to go to shopping at all. It will be interesting to know whether authors have considered this limitation and if yes, why have they not chosen to discuss regarding this in their paper.
References:-
1. Chang Y-H, Chen RC-Y, Wahlqvist ML, et al. J Epidemiol Community Health (2011). doi:10.1136/jech.2010.12669
2. Giridhara R Babu.Do you see an elephant or just its trunk? The need of learning Modern Epidemiologic Methods: An introduction. The Internet Journal of Epidemiology. 2011 Volume 10 Number 1 (Under Print)
As a coffee-drinking virologist, I read Leung et al's report on
coffee consumption and risk of hepatocellular carcinoma (HCC) with
interest[1].
The authors excluded those "under medication for liver diseases". It
is a reasonable assumption that this means that patients who were
receiving antiviral therapy for hepatitis B virus (HBV), e.g. lamivudine,
entecavir etc. were excluded. Because patients...
As a coffee-drinking virologist, I read Leung et al's report on
coffee consumption and risk of hepatocellular carcinoma (HCC) with
interest[1].
The authors excluded those "under medication for liver diseases". It
is a reasonable assumption that this means that patients who were
receiving antiviral therapy for hepatitis B virus (HBV), e.g. lamivudine,
entecavir etc. were excluded. Because patients with a higher risk of
developing HCC tend to receive drug therapy for HBV[2], there is a risk
that the exclusion of HBV carriers on anti-HBV therapy may have introduced
a bias into the non-HCC control group.
Healthy HBV carriers in whom antiviral therapy is not indicated may
be fundamentally different from patients with HBV-related HCC. One would
expect patients who do not meet criteria for initiating antiviral therapy
to have a better prognosis i.e. are less likely to develop HCC.
Leung et al acknowledge some limitations of this study e.g. lack of
HBV viral load data and alanine transaminase (ALT) level. However,
patients' hepatitis B e antigen status, one measure of HBV infectivity and
an independent predictor for progression to HCC[3], is also missing. I
would suggest these limitations have been underplayed.
The absence of HBV viral load data, e antigen status and ALT levels
are significant omissions and linked to my first point about excluding
patients on "medication for liver disease". These variables are both
prognostic indicators and indicators for the necessity for HBV treatment.
Finally, it would be of interest to know the hepatitis C (HCV) and
HIV status of the patients studied, as these do affect the prognosis in
hepatitis B carriers. I concede that both HCV and HIV seem to be
relatively uncommon in Hong Kong[4,5]. As this information was not
provided, yet more potential confounding variables have been left
unaddressed.
The apparent exclusions and omissions detailed above leave
considerable room for doubt about the comparability of the cases and
controls and thus of the conclusions drawn.
The proposition that coffee consumption reduces the risk of HCC
developing in HBV carriers is a seductive one. It would be an almost ideal
public health intervention, as coffee is widely available, economical,
given that the cost is borne by patients and there are few significant
side effects with light or moderate consumption.
Unfortunately, it is difficult to concur with the author's conclusion
that moderate coffee consumption significantly reduces the risk of HCC in
HBV carriers based upon the findings of this study.
References:
1. Leung W W-M, Ho SC et al. Moderate coffee consumption reduces the
risk of hepatocellular carcinoma in hepatitis B chronic carriers: a case-
control study. J Epidemiol Community Health 2011;65:556-558
2. Sung JJ, Amarpurkar D et al. Treatment of chronic hepatitis B in
Asia-Pacific countries: is the Asia-Pacific consensus statement being
followed? Antivir Ther 2010;15(4):607-16
3. Yang HI, Lu SN, Liaw YF et al. Hepatitis B e antigen and the risk
of hepatocellular carcinoma. N England J Med 2002;347(3):168-74
4. Hong Kong Department of Health. Viral Hepatitis Preventive Service
website. http://www.info.gov.hk/hepatitis/english/hep_c_set.htm (accessed
18/7/11)
5. Hong Kong Department of Health. HIV/AIDS Situation in Hong Kong
(2005) factsheet. http://www.info.gov.hk/aids/pdf/g154.pdf (accessed
18/7/11)
The correlation (r = 0.73) between income inequality and prevalence
of mental illness reported by Pickett, James and Wilkinson (2006) was an
intriguing finding, but we should be extremely cautious interpreting it.
First, it was admittedly only a preliminary analysis and hence the
number of data points (countries) was small (n = 8). Consequently, the
correlation estimate will lack precision...
The correlation (r = 0.73) between income inequality and prevalence
of mental illness reported by Pickett, James and Wilkinson (2006) was an
intriguing finding, but we should be extremely cautious interpreting it.
First, it was admittedly only a preliminary analysis and hence the
number of data points (countries) was small (n = 8). Consequently, the
correlation estimate will lack precision and this is reflected in the
confidence intervals for the correlation estimate, 95% CI [0.03, 0.95].
Hence, the correlation estimate could be substantially lower.
Second, referring back to the raw data that originated from the UNDP
Human Development Report (2005) and Demyttenaere et al. (2004) I
discovered that data from the four developing countries (Mexico, Columbia,
Ukraine and Nigeria) was excluding from the original analysis. If we
recomputed the correlational analysis using the original data supplemented
by the data from the four developing countries we obtain a correlation of
0.07 (95% CI [-0.52, 0.62]).
Third, assuming that there are good reasons for excluding the
developing countries, a high correlation between income inequality and
prevalence of mental illness tells only part of the story. What is equally
important is the unstandardized slope of the linear regression line (i.e.,
simple effect size). This is because, though income inequality and
prevalence of mental illness may be highly correlated, the magnitude that
the prevalence of mental illness increases in relation to the income
inequality may be negligibly small. The unstandardized slope of the linear
regression line for the original data from Pickett et al (2006) is 3 (95%
CI [0.12, 5.87]). Therefore, as the income equality, measured in terms of
the ratio of the top 20% to the bottom 20% incomes increases by 1 the
prevalence of mental illness increases by 3%. But what we have to bear in
mind is that a ratio increase of 1 actually represents a 100% increase in
the difference between the top 20% and the bottom 20% incomes. Therefore,
the prevalence of mental illness increases by only 3% when the difference
between the top 20% and the bottom 20% incomes increases by 100%. Or in
other words 1% increase in the difference between the top 20% and the
bottom 20% incomes is associated with a 0.03% increase in the prevalence
of mental illness. Hence, the impact of income equality on the prevalence
of mental illness appears to be, as one would expect, relatively small.
References
Demyttenaere K, Bruffaerts R, Posada-Villa J, et al. (2004).
Prevalence, severity, and unmet need for treatment of mental disorders in
the World Health Organization world mental health surveys. JAMA, 291, 2581
-90.
Pickett, K.E., James, O.W., & Wilkinson R.G. (2006). Income
inequality and the prevalence of mental illness: a preliminary
international analysis. Journal of Epidemiology & Community Health,
60, 646-647.
United Nations Development Programme. (2005). Human Development
Report. New York: Oxford University Press. Retrieved from:
http://hdr.undp.org/en/media/HDR05_complete.pdf
We read with interest the article describing methods for modelling count data with excess zeros compared to standard count distributions, such as Poisson1. This topic has been extensively discussed in the statistical and epidemiological literature2-3. Didactic messages given by statisticians can often lack an appreciation of the epidemiological context and sadly this article has the same shortcomings.
The primary novelty is t...
We read with interest the article describing methods for modelling count data with excess zeros compared to standard count distributions, such as Poisson1. This topic has been extensively discussed in the statistical and epidemiological literature2-3. Didactic messages given by statisticians can often lack an appreciation of the epidemiological context and sadly this article has the same shortcomings.
The primary novelty is the context in which the issue is discussed: application to counts of Activities of Daily Living (ADL-s). It is laudable that methodological issues are tackled using practical examples, but our concern is that the novel context has been largely overlooked and an educational opportunity lost. The message is too narrow in scope and arguably misleading. The reader is told that the zero-inflated Negative Binomial is the most appropriate model for the ADL-s data, yet this is likely incorrect and could lead to inappropriate models being adopted in this domain.
The Binomial distribution deals with bounded data and is extended to yield the Beta Binomial, which accommodates overdispersion. Both the Binomial and Beta Binomial distributions have zero-inflated extensions (e.g. the "zero-inflated Binomial") to account for an excess of zeros4. We were surprised to see no mention of these alternative distributions since the Poisson distribution exhibits an infinite tail and predicts counts in excess of six, albeit with low probabilities. Allowing for over-dispersion, the Negative Binomial accommodates a longer tail for the same mean. Both distributions (whether zero-inflated or not) thus possess properties that are incongruent with the nature of the data in this context.
Any count distribution assumes an increment of one has the same meaning from one to two as from five to six; for zero-inflated extensions, the increment from zero to one may have a different meaning. As each ADL-s is unique, each is likely to have a different meaning. Hence, as individuals deteriorate in their condition, some activities may become a challenge before others. Consequently, an increment of one ADL may have different meaning along the scale and it is sensible to assume an ordinal outcome5, which also accommodates differences in the increment from zero to one.
Good agreement between observed and predicted outcomes is necessary but not sufficient. Disparity between models with regard to predicted outcomes can often be negligible whilst models differ substantially in parameterisation and hence interpretation. Likelihood-based model-fit criteria are only one facet of model development; context validity and interpretability must also have a bearing and researchers must appreciate the context in which data are generated. For this reason the best model may not yet have been found. We have not investigated the dataset, nor do we feel the need to do so when proposing the ordinal model and only with no compelling evidence that increments differed might we instead propose the zero-inflated Binomial or Beta Binomial for parsimony.
References
1. Zaninotto P, Falaschetti E. Comparison of methods for modelling a count outcome with excess zeros: application to Activities of Daily Living (ADL-s). J Epidemiol Community Health 2011; 65: 205-210.
2. Lambert D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics 1992; 34:1–14.
3. Gilthorpe MS, Frydenberg M, Cheng Y, Baelum V. Modelling count data with excessive zeros: The need for class prediction in zero-inflated models and the issue of data generation in choosing between zero-inflated and generic mixture models for dental caries data. Statistics in Medicine 2009; 28: 3539-3553.
4. Vieira AMC, Hinde JP, Demetrio CGB. Zero-inflated proportion data models applied to a biological control assay. Journal of Applied Statistics 2000; 27:373–389.
5. Lall R, Campbell MJ, Walters SJ, Morgan K and MRC CFAS Co-operative. A review of ordinal regression models applied on health-related quality of life assessments. Stat Methods Med Res 2002; 11: 49-67.
There is much evidence linking learning and behaviour problems in
childhood to refined oils in the maternal diet during pregnancy and
lactation, particularly linoleic acid in both cis and trans forms which
may impair fetal brain development. A lower IQ in these children would
not be surprising.
I have seen no evidence, however, linking fresh natural fats to any
of these problems. Diets high in refined sugars...
There is much evidence linking learning and behaviour problems in
childhood to refined oils in the maternal diet during pregnancy and
lactation, particularly linoleic acid in both cis and trans forms which
may impair fetal brain development. A lower IQ in these children would
not be surprising.
I have seen no evidence, however, linking fresh natural fats to any
of these problems. Diets high in refined sugars tend to be high in
refined oils as well -- the two go together -- so I think it's important
to stress that "high fat" in this case refers only to processed oils, not
the healthy fats naturally present in fresh whole foods.
I would be pleased to provide references re linoleic acid and effects
on offspring to anyone wishing to contact me at the address above.
Dear Editor
In their recent paper, Smith and Katikireddi (2012) provide a useful outline of theories for understanding policymaking. The article is aimed at public health practitioners and researchers who are seeking to shape policy. It rightly encourages them to draw on relevant theory to more productively guide their interactions with, and potential influence on, relevant policy. This is a timely and welcome...
The aim of the authors was to assess the validity and agreement of self-reported prevalent cases of stroke and AMI in the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC). They calculated sensitivity, specificity, positive predictive values and ? statistics. The sensitivity of self-reported prevalent cases of stroke was 81.3% and that for AMI was 97.7%. The positive predictive value...
I was interested to read your letter/article in the Journal of Epidemiology and Community Health, and your conclusion that there were significant reductions in IMR. You wondered whether this might have been due to interventions such as Sure Start and the Health in Pregnancy grant. I would be surprised if the latter played any significant part, as it came far too late in pregnancy to do anything significant and, anecdotally...
Numerous studies conducted have found evidence for a positive relation between green space in peoples environment and self reported indicators of morbidity and mortality (Lee and Maheswaran, 2011). The authors in this study have found mortality from all causes to be higher in greener cities. Attempts have been made to adjust for factors which may act as confounders, however other community level factors have not been tak...
Sir,
As a coffee-drinking virologist, I read Leung et al's report on coffee consumption and risk of hepatocellular carcinoma (HCC) with interest[1].
The authors excluded those "under medication for liver diseases". It is a reasonable assumption that this means that patients who were receiving antiviral therapy for hepatitis B virus (HBV), e.g. lamivudine, entecavir etc. were excluded. Because patients...
Dear Editor,
The correlation (r = 0.73) between income inequality and prevalence of mental illness reported by Pickett, James and Wilkinson (2006) was an intriguing finding, but we should be extremely cautious interpreting it.
First, it was admittedly only a preliminary analysis and hence the number of data points (countries) was small (n = 8). Consequently, the correlation estimate will lack precision...
There is much evidence linking learning and behaviour problems in childhood to refined oils in the maternal diet during pregnancy and lactation, particularly linoleic acid in both cis and trans forms which may impair fetal brain development. A lower IQ in these children would not be surprising.
I have seen no evidence, however, linking fresh natural fats to any of these problems. Diets high in refined sugars...
Pages