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Recent eLetters

Displaying 1-10 letters out of 233 published

  1. TTC places public health at risk

    It cannot be denied that TTC (Threshold of Toxicological Concern) was originally proposed in the U.S., as Dr Harris states in her commentary on our article,[1] but her industry-sponsored organisation, the International Life Sciences Institute (ILSI) played a major role in developing it further to the form in which it was accepted by European Food Safety Authority (EFSA).

    This process took place in an EFSA working group, in which ten out of 13 members had previously developed and promoted the tool with ILSI.[2] While EFSA communicators have attempted damage control in their online Q&A, the biased work on TTC raised such concerns in the European Parliament that EFSA was forced to ban ILSI-linked people from being members of expert panels and working groups. Any link with ILSI now has to be cut in order to qualify as an EFSA expert.

    Apart from this industry infiltration of EFSA, the tool as delivered by ILSI is far from being "scientifically supported", as Dr Harris suggests. The database underpinning the TTC for non-genotoxic substances[3] is entirely made up of (potentially biased) industry studies. Many of these studies are 40-60 years old and non-retrievable (cannot be accessed), meaning that their quality cannot be assessed. In addition, the old protocols used means that current scientific knowledge will not be taken into account in calculating TTCs. In utero exposure is generally missing and important risks will be overlooked because of the limited endpoints considered at that time. The grouping of chemicals for TTC is artificial and is based on the Cramer classification,[4] which relies on expert judgement only and is subjective. ILSI has also manipulated the genotoxin database to get to an apparently desired outcome. For example, it has removed aflatoxin-like, azo- and N-nitroso- substances.[5] Another unscientific shortcoming of TTC is its disregard of cumulative effects.

    The TTC is derived by arbitrarily removing from the calculation the most toxic effects found in the database of NOELs (no adverse effect levels). The TTC sets the 'level of no concern' at the 5th percentile, resulting in a 1 in 20 chance that a random substance in any one group of chemicals is toxic at this exposure level. Thus 5% of the chemicals in the group are more toxic than the 'level of no concern' that is set for any one group of chemicals.

    TTC is promoted as a screening tool while in practice it is already being used as a cut-off criterion (safe level) for pesticide metabolites.[6] Industry is now trying to extend TTC to other fields such as any chemical found in food,[7] outcomes of developmental testing,[8] drinking water,[9] and inhaled chemicals.[10] In many cases, and not coincidentally, advocates of TTC are pursuing these aims through opinions published in Regulatory Toxicology and Pharmacology, the controversial chemical/pharmaceutical industry-sponsored journal. The journal was one of several entities that were investigated by a US Congressional Committee in 2008 over their role in the Food and Drug Administration (FDA) decision allowing bisphenol A in infant formula and other foods.[11-13]

    Analysing the TTC tool and the background of its development can only lead to the conclusion that industry has invested massively in a tool that does not safeguard human health, as Dr Harris misleadingly claims, but exactly the opposite. The tool serves industry's agenda of fast-tracking chemicals to the market and avoids the costs of testing. The tool undermines European legislation and policy. It aims to replace the existing EU policy of 'no safe level' for genotoxic substances with claimed 'safe levels' arrived at through the TTC. It also aims to replace the EU policy that health of citizens should be protected by adequate testing and the precautionary principle with a tool that enables avoidance of testing for chemicals, metabolites and impurities.

    The tool, which serves industry's agenda but places public health at risk, has been introduced into European agencies by people who have served as members of expert panels while maintaining conflicts of interest with industry. Dr Harris's reference to the Danish study[14] as a balanced review of TTC is a case in point. Its author, John Christian Larsen, worked in ILSI scientific bodies from 2002 till 2008[15] and has published studies with ILSI-affiliated people who have promoted TTC.[16] TTC has made its way into the regulatory policy of the food safety authority EFSA because of industry's massive resources and a lack of awareness on the part of EFSA's staff, not for reasons of sound science.

    References

    1. Robinson C, Holland N, Leloup D, et al. Conflicts of interest at the European Food Safety Authority erode public confidence. J Epidemiol Community Health Published Online First: 8 March 2013. doi:10.1136/jech-2012-202185

    2. Muilerman H, Tweedale T. A toxic mixture? Industry bias found in EFSA working group on risk assessment for toxic chemicals, Pesticide Action Network Europe 2011.

    3. EFSA Scientific Committee. Scientific opinion on exploring options for providing advice about possible human health risks based on the concept of Threshold of Toxicological Concern (TTC). EFSA Journal 2012;10: 2750.

    4. Cramer GM, Ford RA, Hall RL. Estimation of toxic hazard - a decision tree approach. Food Cosmet Toxicol 1978;16: 255-276.

    5. Kroes R, Renwick AG, Cheeseman M, et al. Structure-based thresholds of toxicological concern (TTC): guidance for application to substances present at low levels in the diet. Food Chem Toxicol 2004; 42: 65-83.

    6. European Commission Health and Consumer Protection Directorate- General (DG SANCO). Guidance document on the assessment of the relevance of metabolites in groundwater of substances regulated under Council Directive 91/414/EEC: Sanco/221/2000-rev.10-final. 25 February 2003.

    7. Koster S, Boobis AR, Cubberley R, et al. Application of the TTC concept to unknown substances found in analysis of foods, Food and Chemical Toxicology 2011; 49: 1643-1660.

    8. Van Ravenzwaay B, Dammann M, Buesen R, et al. The threshold of toxicological concern for prenatal developmental toxicity. Regulatory Toxicology and Pharmacology 2011;59: 81-90.

    9. Melching-Kollmuss S, Dekant W, Kalberlah F. Application of the ''threshold of toxicological concern" to derive tolerable concentrations of ''non-relevant metabolites" formed from plant protection products in ground and drinking water. Regulatory Toxicology and Pharmacology 2010; 56: 126-134.

    10. Escher SE, Tluczkiewicz I, Batke M, et al. Evaluation of inhalation TTC values with the database RepDose. Regulatory Toxicology and Pharmacology 2010; 58: 259-274.

    11. Michaels, D. Doubt Is Their Product: How Industry's Assault on Science Threatens Your Health. Oxford University Press. 2008: 53-54.

    12. Layton L. Studies on chemical in plastics questioned. Washington Post 27 April 2008.

    13. Dingell JD. Letter to Jack N Gerard, president and CEO, American Chemistry Council. 2 April 2008. http://bit.ly/ZWMbi6 (accessed 15 April 2013).

    14. Nielsen E, Larsen JC. The Threshold of Toxicological Concern (TTC) concept: Development and regulatory applications. Danish Ministry of the Environment, Environmental Protection Agency. Environmental Project No. 1359. 2011. http://www2.mst.dk/udgiv/publications/2011/03/978-87-92708 -86-1.pdf (accessed 15 April 2013).

    15. European Food Safety Authority (EFSA). Declarations of interests (DoIs). http://www.efsa.europa.eu/en/efsawho/doi.htm (accessed 15 April 2013).

    16. Pratt I, Barlow S, Kleiner J, et al. The influence of thresholds on the risk assessment of carcinogens in food. Mutation Research 2009; 678: 113-117.

    Conflict of Interest:

    Hans Muilerman is employed at Pesticide Action Network Europe, which receives funding from trusts and foundations, including the European Endocrine Health Initiative.

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  2. Science-based tools for public policy development are critical

    I am responding on behalf of the International Life Sciences Institute (ILSI) to the Commentary published on Online First on 8 March 2013: "Conflicts of interest at the European Food Safety Authority erode public confidence" by Robinson et al.

    In their Commentary, the authors raise questions about practical scientific tools being studied by a variety of private and public sector groups, including the European Food Safety Authority (EFSA). EFSA has previously and thoroughly responded to the questions posed by the authors on plant biotechnology; the Threshold of Toxicological Concern (TTC) concept; and scientific integrity.(1) My goal is to address the specific section of the Commentary under the heading "EFSA Promotes Industry Concept to Assess Chemicals Risk" by providing additional context on TTC as a risk assessment tool.

    The concept underlying TTC was initially proposed in 1967(2) and formally articulated by the US Food and Drug Administration in 1986(3). It was developed to identify, characterize, and prioritize risk when data on substances of concern were extremely limited or nonexistent. As the authors state, ILSI has supported a number of activities designed to test the validity of the TTC approach since then, and we have worked with industry and public partners to hone the tool as more data becomes available.

    We encourage JECH readers to learn more about the TTC concept by reading the report "The Threshold of Toxicological Concern (TTC) concept: Development and regulatory applications."(4) This document, produced by the Danish Ministry of the Environment, Environmental Protection Agency and available in English, provides an extremely comprehensive, detailed, and readable review of the TTC concept's scientific principles; its development over the years; its current uses; and its strengths and weaknesses.

    ILSI's actions on TTC have been with the primary goal to help improve response to safety assessment needs in situations when it is analytically difficult to identify a substance or when an assessment is needed urgently and existing data are insufficient. We fully recognize TTC is not a blanket solution and our own publications describe its limitations.(5) However, to diminish well-studied, scientifically supported tools that can be used to safeguard human health is both inappropriate and irresponsible.

    1 EFSA Answers Back. Online Q&A. http://www.efsa.europa.eu/en/news/efsaanswersback.htm

    2 Frawley JP (1967). Scientific evidence and common sense as a basis for food packaging regulations. Fd Cosmet Toxicol 5, 293-308.

    3 Rulis AM (1986). De minimis and the threshold of regulation. In: Felix CW (Ed.) Food Protection Technology. Lewis Publishers Inc., Chelsea, Michigan, 29-37.

    4 Nielsen E and Larsen JC (2011). The Threshold of Toxicological Concern (TTC) concept: Development and regulatory applications. Danish Ministry of the Environment, Environmental Protection Agency. Environmental Project No. 1359 2011. This report can be downloaded at http://www2.mst.dk/udgiv/publications/2011/03/978-87-92708-86-1.pdf online.]

    5 Koster S et al. (2011). Application of the TTC concept to unknown substances found in analysis of foods . Food Chem. Toxicol. 1643 - 1660.

    Conflict of Interest:

    I am employed by the International Life Sciences Institute, which is primarily funded by the food, drug, and agriculture industries.

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  3. Present self-reported physical activity and objective physical activity in the future

    Hamer et al. conducted a 13-year longitudinal study on the predictive ability of self-reported physical activity on physical activity measured by accelerometers (1). Participants were 394 healthy men and women aged 54 years on average. They concluded that the habits of physical activity in adulthood are partly tracked into older age. About their attractive report, I have several concerns on their statistical outcomes.

    First, Hamer et al. categorized self-reported physical activity into four groups, and analysis of variance on accelerometer-derived physical activities was made by adjusting several confounders. They adopted general linear models as multivariate analysis in combination with correlation coefficient (CC). Although they concluded their outcome from that statistical significance, the level of association presented by CC was weak and there was no presentation of explanation rate to predict accelerometer-derived physical activities from multivariate analysis.

    Second, I appreciate their long term follow-up of the target participants, but their analysis was the trend analysis, presenting that groups who declared high levels of self-reported physical activity subsequently showed high objective physical activity on average. On this point, individual agreement of physical activity over 13 years should be presented such as intra-class CC, concordance CC and the Bland-Altman plot, which would improve the quality of study.

    Third, I understand that the self-reported physical activity and objective physical activity by accelerometers have different meaning on activity monitoring (2). If the authors assume the physical activity by accelerometers as a gold standard, please present validation data for the accelerometer around the waist to monitor physical activity. Relating to the selection of indicators on physical activity, predictive ability of self-reported physical activity for the same indicator after 13 years is also a simple and understandable for their study. In this case, (weighted) kappa statistics would become useful statistical indicator for the agreement.

    Anyway, caution should be paid on the validity of accelerometer as a monitoring tool for physical activity or sedentary behaviour from mid-life to early old age (3).

    References

    1. Hamer M, Kivimaki M, Steptoe A. Longitudinal patterns in physical activity and sedentary behaviour from mid-life to early old age: a substudy of the Whitehall II cohort. J Epidemiol Community Health 2012;66:1110-5.

    2. Martinez-Gomez D, Gomez-Martinez S, Ruiz JR, et al. Objectively- measured and self-reported physical activity and fitness in relation to inflammatory markers in European adolescents: the HELENA Study. Atherosclerosis 2012;221:260-7.

    3. Evenson KR, Buchner DM, Morland KB. Objective measurement of physical activity and sedentary behavior among US adults aged 60 years or older. Prev Chronic Dis 2012;9:E26.

    Conflict of Interest:

    None declared

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  4. Traffic Pollution may Increase Testosterone which may Increase Preeclampsia

    "Traffic-related pollution," especially diesel combustion produced, may be shown to increase testosterone. It is my hypothesis that increased maternal testosterone increases preeclampsia (http://anthropogeny.com/Incresing%20Testosterone%20and%20Preeclampsia.htm ).

    I suggest the findings of Pereira, et al., may be explained by increased maternal testosterone.

    Conflict of Interest:

    None declared

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  5. Family meals boost children's 5 A Day

    We all know eating together as a family can boost conversation, foster closeness and encourage healthy ways with food. However, a 2011 survey of 1354 people for the insurance firm Cornish Mutual found 48% of British households do not share a meal every day. [1]

    This study shows that by having a family dinner together it can increase children's daily fruit and vegetable intake to reach the 5 A Day target. It reinforces the view that children learn more from what adults do than what they say, therefore it is the parental role modelling that helps shape their future habits.

    The strengths of this study are its large sample size (2383 children) and reliable methods of assessing dietary intake through a validated food intake tool. However, there are limitations which have not been noted by the researchers.

    This is a single sample of London schoolchildren taking part in trials assessing school gardening and diet. We do not know whether the children who were taking part in this trial may have particular characteristics that make them different from, for example, children selected from a completely random primary school sample. Also, the children in this London area may not be representative of the entire UK population in terms of culture and ethnicity, which may be related to family eating patterns.

    While home environment and parental food attitudes are likely to influence the child's food intake, there may be other factors such as children's preference, social factors or peer pressure. One or a combination of these factors could directly influence the child's food intake.

    In the United States, the month of October is the national "Eat Better, Eat Together Month". [2] A tool kit has been developed to promote family meal time. [3]

    If your family isn't already making dining together a priority, now is the perfect time to start!

    REFERENCES

    1. Deborah Clark Associates. Press release: Half of UK families are not eating together. 24 February 2011. http://www.dca-pr.co.uk/Latest- News/Cornish-Mutual/Half-of-UK-families-are-not-eating-together-123.aspx

    2. Healthy Meals Resource System. Eat Better, Eat Together Month. http://healthymeals.nal.usda.gov/features-month/october

    3. Washington State University Nutrition Education. Eat Better, Eat Together Tool Kit. http://nutrition.wsu.edu/ebet/toolkit.html

    Conflict of Interest:

    None declared

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  6. Policy, evidence and theory; contextualising a glossary of policymaking

    We welcome the glossary of theories presented last month by Smith & Katikireddi (2012) and applaud the intention to introduce wider thinking from the political sciences on these subjects to health researchers. Drawing on our practical experiences in the fields of healthcare management and health services research, we would like to identify three related areas which may also be useful for the public health audience. We suggest this commentary solely to help the glossary to be more widely used and increase its impact.

    Firstly, although several useful definitions of policymaking are described, we feel that 'policy' tends to be interpreted too broadly by public health practitioners, and narrowing down the definition of policy in relation to the concepts of 'management' and 'governance' might be useful. Management' refers to the organisation and leadership of practice, and is primarily concerned with execution and implementation(Mitchell & Shortell, 2000)). 'Governance' in non-profit contexts most frequently refers to the funding and oversight roles of government agencies (Provan & Kenis, 2008). We believe that understanding the differences between policy, management and governance are essential for public health researchers to explore how public health, and indeed health services and public policy more generally operate and can be influenced. As it stands, the glossary predominantly focuses on policy, rather than management and governance. However, the theories of policymaking should not be blindly transferred to the fields of management and governance as these are often concerned with policy implementation, rather than policymaking.

    Secondly, the glossary notes the existence of knowledge brokerage and policy entrepreneurship, which are part of a wider debate about how policy is made, and the role of evidence in policy making. The degree to which research evidence can, should and actually is used in policy making has been an area of extensive debate, and it is worth highlighting a number of seminal sources dealing with these issues. Nutley, Walter and Davies describe the importance of evidence use by policy makers (Nutley et al., 2007). Much of the work in this area is informed by the work of Carol Weiss (1979) with her helpful categorisation of the meanings of research utilisation into seven categories: as' knowledge-driven', 'problem solving', 'interactive' 'enlightenment', 'political',' tactical' 'instrumental', and 'research as an intellectual enterprise'(Weiss, 1979). More recently, Lomas and colleagues have contributed the 'linkage and exchange' model, focusing on relationships between researchers and policymakers, now acknowledged to be a fundamental part of knowledge translation (Lomas & Brown, 2009). Ray Pawson and colleagues have worked extensively on bringing realist interpretations to the use of evidence in policy (Greenhalgh et al., 2004; Pawson, 2006). More recently, a more critical stance about the definitions and uses of evidence has been taken by Marston and watts (Marston & Watts, 2003)) with the impact of evidence-use on population outcomes also in doubt (Macintyre, 2003).

    Thirdly and finally, we note that the impetus for producing the glossary was an observation that "public health's efforts to influence policy often appear to be uninformed by the empirically-based theories about policymaking developed within social and political sciences". We welcome the focus on empirically-led theory, but questions remain about the extent to which the models and rhetoric around policymaking are indeed data-, as opposed to theory-driven. While it is true that many models of policy making exist, we believe that it is not clear whether models are employed analytically to understand empirical datasets, or tested across different scenarios. This would be a useful exercise for all researchers interested in evidence-based policy.

    Reference List

    Greenhalgh, T., Robert, T., MAcfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of Innovations in Service Organizations: Systematic Review and Recommendations. The Milbank Quarterly, 82.

    Lomas, J. & Brown, A. D. M. A. (2009). Research and advice giving: A functional view of evidence-informed policy advice in a Canadian ministry of health. [References]. Milbank Quarterly., 87, 903-926.

    Macintyre, S. (2003). Evidence based policy making. BMJ, 326, 5-6.

    Marston, G. & Watts, R. (2003). Tampering with the evidence: A critical appraisal of evidence-based policy-making. The Drawing Board: An Australian Review of Public Affairs, 3, 143-163.

    Mitchell, S. & Shortell, S. (2000). The Governance and Management of Effective Community Health Partnerships: A typology for Research, Policy and Practice. The Milbank Quarterly, 78, 241-289.

    Nutley, S., Walter, I., & Davies, H. T. O. (2007). Using Evidence: How Research Can Inform Public Services. The Policy Press.

    Pawson, R. (2006). Evidence-based Policy.

    Provan, K. G. & Kenis, P. (2008). Modes of Network Governance: Structure, Management, and Effectiveness. Journal of Public Administration Research and Theory, 18, 229-252.

    Weiss, C. H. (1979). The Many Meanings of Research Utilization. Public Administration Review, 39, 426-431.

    Conflict of Interest:

    None declared

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  7. Policy-as-discourse - an additional theory that makes for a more comprehensive glossary

    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 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.

    Conflict of Interest:

    None declared

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  8. What leads to a healthy ageing and longevity?

    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.

    Conflict of Interest:

    None declared

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  9. Validity of self-reported prevalent cases of stroke and acute myocardial infarction in the Spanish cohort of the EPIC study

    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

    Conflict of Interest:

    None declared

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  10. Health inequalities and IMR

    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.

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