299 e-Letters

  • PACE - Not the Nation's Quick Fix

    Dear Editor,

    Much has been published in the news as of late about the effects of physical activity calorie equivalent (PACE) food labelling in order to reduce the nation’s calorie consumption. These labels aim to identify how many minutes of physical activity are required to burn off the calories in a particular food item. A systematic review and meta-analysis, by researchers at Loughborough University, found that food labelling may reduce the number of calories consumed compared with food that was not labelled or other types of food labelling (1).
    This was supported by the UK Royal Society for Public Health which had already advocated for PACE to replace the current labelling system (2). Overall, it found this technique could lead to a reduction of 100 calories per day combined with an increase in physical activity.

    Many nutritionists have been quick to criticise, stating that it loses sight of the fact that food goes beyond calories and is fundamental for social aspects of life (3). Additionally, the nutritional content of food might be neglected. For example, it might be easier to “burn off” a chocolate bar than something with much more nutritious such as nut butters or a banana. This could result in people picking the easier but not necessarily the “healthier option.” Digestion is complex and although foods such as nuts and oats might be high in calories, their content results in slower processing and digestion. This allows people to feel fuller fo...

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  • Creating small-areas deprivation indices at a European level

    In their article (1) Allik et al. proposes a very interesting contribution on the principles and options for the construction of deprivation indices. About weighting indicators, they referred to the European deprivation index (EDI), an index aiming at using a unique methodology for all European Union, and advised to rather be “guided by theory and the specific context of each country” than data-driven. We totally agree that deprivation indices need to be theory driven. The construction of EDI is then guided by this approach. EDI is indeed based on the fundamental concept of relative poverty defined by the material impossibility of accessing basic needs that correspond to the average standard of living in a given country. This theoretical development was proposed by Townsend and Gordon in various publications at the end of the 20th century. In order to propose a measure of relative poverty that should be as comparable as possible between European countries, these basic needs have been defined specifically in each country from the same European database (EUSILC) with the same methodology.
    This country–specific basics needs were then tested through regression analyzes to make sure that they were well correlated with objective and subjective poverty, here again specifically in each country, and that additivity, validity and reliability were preserved. Finally, we selected by regression analysis the country-specific combination of features the most correlated to these bas...

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  • Re: Mortality inequalities by occupational class among men in Japan, South Korea and eight European countries: a national register-based study, 1990–2015

    As Prof. Young-Ho Khang points out, numerator-denominator bias may affect the estimation of mortality for the Korean and Japanese populations, because we used a cross-sectional unlinked design.[1] We mentioned the possibility of this bias in our paper, citing a study from Lithuania, which suggests that the mortality of persons with high socioeconomic status may be underestimated as a result of this bias.[2] However, based on a national validation study Prof. Khang suggests that the direction of this bias may work the other way around in the Korean population.[3] Furthermore, because – according to his information – the registration of occupation has changed in South Korea, Prof. Khang also claims that the deterioration of the mortality rates among upper non-manual workers observed in our paper is likely to be an artefact.
    While we agree with Prof. Khang that the direction of the numerator-denominator bias may be different in South Korea as compared to Lithuania, we do not agree that the ‘reverse’ manual/non-manual mortality rate ratio that we found in South Korea can be explained by this bias, or that the unfavourable mortality trends among upper non-manual workers that we observed in South Korea can be explained by a change in registering occupation. Our findings prior to 2005 are similar to those of a longitudinal study that followed participants between 1995 and 2008 and reported low mortality among male managers and professional workers in South Korea.[4] Our stu...

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  • The surprising result of manual workers in Korea enjoying lower mortality than non-manual workers is likely due to numerator-denominator bias

    I read with great interest the article by Tanaka and colleagues [1], which examined occupational inequalities in mortality in Korea and reported the surprising result that manual workers in Korea enjoyed lower mortality than non-manual workers. The authors employed unlinked data from Japan and Korea, with population denominators from census data and mortality numerators from death certificates. This type of unlinked data is prone to numerator-denominator bias. A prior Korean study examined the reliability of occupational class between survey and death certificate data using individually linked data from the Korea National Health and Nutrition Examination Survey (KNHANES), clearly showing this possibility [2]. Among 104 deaths of KNHANES participants aged 30-64, the number of deaths among non-manual workers increased from 8 in the survey data to 12 in the death certificate data, while the number of deaths among manual workers decreased from 59 in the survey data to 41 in the death certificate data [2]. The number of deaths in other groups (corresponding to ‘inactive or class unknown’) increased from 37 to 51. Therefore, using unlinked data may result in increased mortality estimates among non-manual workers and other groups and reduced mortality estimates among manual workers [2]. It should be noted that, in Appendix Table 1-2 of the article by Tanaka and colleagues [1], the ‘inactive or class unknown’ group accounted for 44%-51% of total deaths in the most recent 10 years...

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  • Developing obesity prevention policy in Nigeria: what do we need to know?

    Dear Editor,

    We read with interest the paper ‘Prevalence and sociodemographic determinants of adult obesity: a large representative household survey in a resource-constrained African setting with double burden of undernutrition and overnutrition’(1). Chigbu et al., (2018) provide valuable data on obesity prevalence among adults in Enugu State in Nigeria and recommend using their information for the development of Nigerian obesity prevention policy (1). However, the authors do not explore the limitations of their data when recommending its use for development of health policy. We focus our discussion on the limitations of this data.

    Firstly, Chigbu et al collected data in Enugu State, which is only one of 36 states in Nigeria and the obesity prevalence is likely to differ in other states (2). Kandala and Stranges (2017) reported obesity prevalence among women in Nigeria varies considerably between states (2). South-eastern states of Nigeria generally have higher female obesity rates than northern and western states (2). We recommend that the differences in obesity prevalence across Nigeria be considered when using the data in Enugu State to inform obesity prevention policy.

    Secondly, they have collected anthropometric measurements and sociodemographic information, but not nutrition and physical activity data. Overnutrition and physical activity data is important for obesity prevention and research on this is limited in Nigeria. The Demographic Health S...

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  • Ethnic disparity in risk of SIDS and other unexplained infant death is not due to deprivation; examining ethnic patterns may help to clarify aetiology

    We thank Professors Bartick and Tomori for their comments on our paper. [1] We entirely agree that unexplained death in infancy (UDI) in the (mainly White British) general population of England and Wales is strongly associated with deprivation, as shown by many previous studies. Clearly, any factor that is associated with deprivation among the White British group will be a risk factor for UDI in the general population.

    However, our paper is about ethnic, not socio-economic, variation. [2] The finding of a nearly five-fold disparity in risk across ethnic groups in England and Wales is both striking and novel. Moreover, we demonstrate that this disparity is not explained by deprivation. Formal adjustment for deprivation (IMD quintiles) does not even slightly reduce the ethnic variation (see Table 2). A simple scatter plot of ethnic groups illustrates the lack of a relationship between deprivation and risk, with a virtually horizontal overall trend line (see Figure at https://doi.org/10.5287/bodleian:XmE4XBaoZ). For example, Black Caribbean babies have nearly triple the UDI risk of Black African babies, but similar levels of deprivation. The Indian, Pakistani and Bangladeshi ethnic groups each have around half the UDI risk of White British babies; the White British and Indian groups have similar (relatively low) levels of deprivation, and the Pakistani and Bangladeshi groups are the most deprived in England and...

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  • Deprivation is the most striking finding of this study; other known risk factors must be explored to explain ethnic variation

    We read with interest the article by Kroll et al., “Ethnic variation in unexplained death in infancy, including sudden infant death syndrome (SIDS), England and Wales 2006-12: national birth cohort study using routine data”[1]. While the five-fold disparity in death rates across ethnic groups is notable, the most striking finding was marked association of infant death with deprivation seen in Table 1, with an OR of 3.45 (95% CI 2.82-4.23) between the most deprived group and the least deprived group. Indeed, 69% of deaths were found in the two most deprived quintiles. The analytical attention on ethnic variation in the paper overshadows the central finding that the majority of risk is driven by poverty.

    Furthermore, unmarried status is a potent indicator of socioeconomic status that may cluster with poverty, lack of social support and experiences of racial discrimination. The remaining variation that the paper attributes to possible cultural variation must be broken down into specific known risk factors, such as tobacco exposure, sleep position, preterm birth, alcohol and substance abuse, lack of prenatal care, formula feeding, sofa sharing, and the combination of bedsharing with these other risk factors[2].These known risk factors are also largely clustered around poverty. Even sleep position is indirectly associated with poverty via formula feeding, as videographic data show that bedsharing formula feeding infants are more likely to assume hazardous sleep position...

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  • Response to Question on Charging for NHS care

    We congratulate the authors on this timely and interesting study: ‘Political views of doctors in the UK: a cross-sectional study’ [1]. We address Question 12, asking whether doctors agree that ‘Patients should be charged for non-urgent care if they are not eligible for free NHS treatment’.
    The authors correctly state that agreement does not mean support for current NHS charging regulations, not least because the most recent amendments in England were introduced after this questionnaire (October 2017 [2]), however we remain concerned about potential misinterpretation, and suggest aspects of charging regulations where doctors’ opinions could be further explored.
    Firstly, the question, which understandably echoes government policy language on charging, is similar to asking ‘Should people have to pay for things that are not free?’ without addressing complexity of eligibility, and the fact that some people living in the UK have lost their eligibility with recent regulations. An assessment of opinions would require measuring knowledge of charging and its relationship with immigration enforcement, as well as evaluating acceptance of the immigration system itself, as this now determines eligibility. Windrush patients being denied NHS treatment highlighted the complexity of this issue [3].
    Secondly, doctors’ opinions on measures which penalise and threaten patients if they seek care, such as linking unpaid NHS debt to immigration enforcement [4], and NHS data shar...

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  • An intervention, not an accident: Research into use of force by police requires understanding its context and counterfactuals

    In “Years of life lost due to encounters with law enforcement in the USA, 2015–2016,” Bui et al. estimate the public health impact of police use of force by a simple computation of the years of life lost by the people killed by police.[1] Unnecessary use of force by police is a problem demanding serious attention, and leadership in policing has responded with interventions and training in recent years to improve de-escalation techniques and reduce the incidence of unnecessary or unlawful use of force. Bui et al.’s analysis, however, fails to consider three key factors in these analyses: first, the distinction between necessary and unnecessary/unlawful uses of force; second, the potential impacts on years of life lost had the police not have intervened in these specific scenarios; and third, the broader impacts of police intervention on public health.
    Police may use lethal force when they have sufficient reason to believe that a person poses a risk of serious physical injury or death to another person. A reporter for The Washington Post concludes that “the vast majority of individuals shot and killed by police officers… were armed with guns and killed after attacking police officers or civilians or making other direct threats.”[2] Unnecessary or unjustified use of force by police are thought to account for about five percent of the total number of incidents of use of force,[2] with great skeptics acknowledging they are certainly fewer than 50%.[3] Including sensitivit...

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  • Length of Life is Affected by the Whole of Your Life

    It is bittersweet to see one’s predictions of a fall in life expectancy coming into being.
    I work on statistics, but also talk to patients regularly about their diets, lifestyles and
    environments. The medical service struggles to deal with the results of poor diet and
    pollution. Perhaps it is time for a health service to deal with the causes of illness.

    Ancel Keys crusaded against fats. He cherry picked data from only 6 of the available
    22 countries. Sugar was then used to make low fat food palatable. Fructose and
    galactose, in sugar, milk, corn syrup and fruit, are implicated in cancer, heart disease,
    dementia and diabetes.

    Are the NHS and social care the priorities? Perhaps money to buy good food is more
    important, and maybe we have too much medicine, not too little. I have seen patients
    taking up to 29 different drugs. No pharmacologist can work out how they interact.
    One patient took 5 drugs for his asthma. People complain of drug side effects and are
    just given more drugs to deal with these symptoms.

    The Depression was forgotten, and it was assumed we could keep becoming richer,
    until 2008. Similarly we cannot just extrapolate the increasing life expectancy figures.
    Public health improved after building reservoirs, chlorinating water, installing sewage
    systems, reducing overcrowding and setting up smokeless zones.

    However, chemical production has increased greatly...

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