We read with interest, intrigue and concern the findings reported in this short report. if the findings are validated from larger and multicentric data this may have huge implications in the way we trace and isolate the COVID-19 contacts. Pre symptomatic transmission from index cases 5 days prior to the onset of symptoms is a huge logistical nightmare in terms of containment strategies. This would imply at practical impossibility and futility of these strategy especially in setting of cluster or community transmission. This also highlights the virtues of basic but universal measures like physical distancing, hygiene and use of mask at all times under specific settings.
The question “Why does Russia have such high cardiovascular (CV) mortality rates?”1 can be answered by a pathologist who practiced during the Soviet time.2 Since then, the quality of post mortem examinations has decreased especially during the 1990s: autopsies were sometimes made perfunctorily. The deterioration in anatomic pathology and the health care in general during the 1990s coincided with the increase in the registered CV mortality. A tendency to over-diagnose CV diseases is generally known to exist also for people dying at home and not undergoing autopsy. If a cause of death is not entirely clear, it has been usual to write on a death certificate: “Ischemic heart disease with cardiac insufficiency” or a similar formulation.2 Concerning the relatively high CV mortality in Russia, it should be commented that irregular treatment of hypertension,3 diabetes and other chronic diseases continues to be a problem. Considering the above, the differences between Norwegian and Russian cohorts1 can be better understood. The levels of serum lipids were comparable between Russia and Norway being slightly higher in the latter possibly due to better nutrition. Interestingly, N-terminal pro-b-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and high-sensitivity C-reactive protein (hsCRP) were higher in Russia.1 It can be reasonably assumed that average levels of these markers inversely correlate with a nation’s health reflected by the life expecta...
The question “Why does Russia have such high cardiovascular (CV) mortality rates?”1 can be answered by a pathologist who practiced during the Soviet time.2 Since then, the quality of post mortem examinations has decreased especially during the 1990s: autopsies were sometimes made perfunctorily. The deterioration in anatomic pathology and the health care in general during the 1990s coincided with the increase in the registered CV mortality. A tendency to over-diagnose CV diseases is generally known to exist also for people dying at home and not undergoing autopsy. If a cause of death is not entirely clear, it has been usual to write on a death certificate: “Ischemic heart disease with cardiac insufficiency” or a similar formulation.2 Concerning the relatively high CV mortality in Russia, it should be commented that irregular treatment of hypertension,3 diabetes and other chronic diseases continues to be a problem. Considering the above, the differences between Norwegian and Russian cohorts1 can be better understood. The levels of serum lipids were comparable between Russia and Norway being slightly higher in the latter possibly due to better nutrition. Interestingly, N-terminal pro-b-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and high-sensitivity C-reactive protein (hsCRP) were higher in Russia.1 It can be reasonably assumed that average levels of these markers inversely correlate with a nation’s health reflected by the life expectancy at birth. Indeed, elevated C-reactive protein is known to be associated with various inflammatory conditions. The natriuretic peptide (NP) plays an important role by opposing the vasoconstriction and sodium retention. A plasma NP elevation was found in essential hypertension, decreasing with effective antihypertensive therapy.4 Hs-cTnT is a biomarker for myocardial damage; but other conditions are also associated with its enhanced level: diabetes, COPD, decreased renal function, anaemia etc.5 The insufficient access to modern healthcare,1 higher consumption of alcohol and cigarettes in Russia vs. Norway (the data can be found in Wikipedia), as well as relatively poor quality of alcohol sold in Russia,6 have probably contributed to a higher morbidity. In conclusion, the valuable results by Dr. Iakunchykova and co-workers1 should motivate further search for associations between NT-proBNP, hs-cTnT and other markers with various pathological conditions.
REFERENCES
1. Iakunchykova O, Averina M, Wilsgaard T, et al. Why does Russia have such high cardiovascular mortality rates? Comparisons of blood–based biomarkers with Norway implicate non-ischaemic cardiac damage. J Epidemiol Community Health 2020;74:698–704.
2. Jargin SV. Cardiovascular mortality trends in Russia: possible mechanisms. Nat Rev Cardiol 2015;12:740.
3. Roberts B, Stickley A, Balabanova D, et al. The persistence of irregular treatment of hypertension in the former Soviet Union. J Epidemiol Community Health 2012;66:1079–82.
4. Hu W, Zhou PH, Zhang XB, Xu CG, Wang W. Plasma concentrations of adrenomedullin and natriuretic peptides in patients with essential hypertension. Exp Ther Med 2015;9:1901–908.
5. Wu W, Li DX, Wang Q, et al. Relationship between high-sensitivity cardiac troponin T and the prognosis of elderly inpatients with non-acute coronary syndromes. Clin Interv Aging 2018;13:1091–8.
6. Jargin SV. Vodka vs. Fortified Wine in Russia: Retrospective View. Alcohol Alcohol 2015;50:624–5.
We read with great interest the report from Hamer and colleagues that examined the hypothesis that associations between television (TV) viewing and mortality from heart disease (HD) are due to confounding (1). They employed a negative control approach (2) and report evidence of associations between TV viewing and HD mortality (HR=1.09 [1.06, 1.12] per 1 hr/day increase in TV) and accidental deaths (the negative control outcome; HR=1.06 [0.98, 1.15]) after adjusting for age, sex, smoking, education, and prevalent HD (1)
The positive association between TV and accidental deaths was interpreted as evidence that the TV-HD mortality association was due to confounding. Although key study limitations were noted including a small number of accidental deaths and limited adjustment for confounding, the authors concluded that “observed associations between TV and HD are likely to be driven by confounding”. Although we agree that confounding is a worrisome threat to the internal validity of epidemiologic studies, we believe that the conclusion in the Hamer report is overstated.
A critical additional strategy to understand bias due to confounding, one that was not employed in the current study, is to examine relevant results from published studies conducted in different study populations using different methods. (2) We previously reported results in two studies that examined associations for accidental deaths and HD mortality with TV viewing (3) and leisure-time sitti...
We read with great interest the report from Hamer and colleagues that examined the hypothesis that associations between television (TV) viewing and mortality from heart disease (HD) are due to confounding (1). They employed a negative control approach (2) and report evidence of associations between TV viewing and HD mortality (HR=1.09 [1.06, 1.12] per 1 hr/day increase in TV) and accidental deaths (the negative control outcome; HR=1.06 [0.98, 1.15]) after adjusting for age, sex, smoking, education, and prevalent HD (1)
The positive association between TV and accidental deaths was interpreted as evidence that the TV-HD mortality association was due to confounding. Although key study limitations were noted including a small number of accidental deaths and limited adjustment for confounding, the authors concluded that “observed associations between TV and HD are likely to be driven by confounding”. Although we agree that confounding is a worrisome threat to the internal validity of epidemiologic studies, we believe that the conclusion in the Hamer report is overstated.
A critical additional strategy to understand bias due to confounding, one that was not employed in the current study, is to examine relevant results from published studies conducted in different study populations using different methods. (2) We previously reported results in two studies that examined associations for accidental deaths and HD mortality with TV viewing (3) and leisure-time sitting (predominantly TV viewing) (4), but these findings were not cited in the Hamer report. Our studies each examined 3-5 times more accidental deaths than the Hamer report, and adjusted for a much larger number of confounding factors. (3,4) We found significant positive associations with TV-HD mortality, but no evidence of association between accidental deaths and greater TV time (HR=1.01 [0.62, 1.64]; 7+ vs. < 1 hr/day) (3) or leisure-time sitting (HR=0.91 [0.76, 1.10]; 6+ vs. < 3 hr/d). (4) In context of the negative control outcome framework, our results provide no evidence that previously observed HD associations, or associations with several other causes of death, were due only to confounding. (3,4)
Many studies have reported positive associations between disease/mortality outcomes and TV, a prevalent leisure-time behavior that, as Hamer and colleagues note, is likely to displace time spent in more healthful physically active pursuits. We strongly support efforts to better understand these relationships, including careful consideration of bias and threats to validity. As we do so, it is critical that we consider the broad range of information available before drawing strong conclusions based on a single study.
References
1. Hamer M, Ding D, Chau J, Duncan MJ, Stamatakis E. Association between TV viewing and heart disease mortality: observational study using negative control outcome. Journal of Epidemiology and Community Health. 2020:jech-2019-212739.
2. Pearce N, Vandenbroucke JP, Lawlor DA. Causal Inference in Environmental Epidemiology: Old and New Approaches. Epidemiology. 2019;30(3):311-316.
3. Keadle SK, Moore SC, Sampson JN, Xiao Q, Albanes D, Matthews CE. Causes of Death Associated With Prolonged TV Viewing: NIH-AARP Diet and Health Study. American Journal of Preventive Medicine. 2015;49(6):811-821.
4. Patel AV, Maliniak ML, Rees-Punia E, Matthews CE, Gapstur SM. Prolonged Leisure Time Spent Sitting in Relation to Cause-Specific Mortality in a Large US Cohort. American Journal of Epidemiology. 2018;187(10):2151-2158.
Dear Editor,
The authors of “Effects of physical activity calorie equivalent food labelling to reduce food selection and consumption: systematic review and meta-analysis of randomized controlled studies” make a strong claim that PACE food labeling can increase consumer consciousness of calorie consumption and therefore caloric reduction, but perhaps this concept deters true understanding of "healthful eating" and may have larger health implications for those with disordered eating.
There is a growing knowledge that that not all calories are created equal. Different foods may not only have different effects on hunger and satiety but also insulin production, gut microbiome interactions, and de novo lipogenesis in the liver (1). While not all consumers need this level of understanding, but without a basic acknowledgement of food’s qualities- like fats, fiber, sugar, ect- the consumer is lead to believe that calories are the most important determinant in what makes food “healthful.” With PACE food labeling, a consumer is led to believe that an ice cream cone and a handful of nuts, both of which could amount to 200 calories, are “equal.” However, in this comparison, only the nuts are possibly advantageous to people with diabetes and cardiovascular disease (2).
Stripping foods down to solely their caloric energy through PACE food labeling could inadvertently foster unhealthy relationships with food. As stated in the article, PACE labeling could be use...
Dear Editor,
The authors of “Effects of physical activity calorie equivalent food labelling to reduce food selection and consumption: systematic review and meta-analysis of randomized controlled studies” make a strong claim that PACE food labeling can increase consumer consciousness of calorie consumption and therefore caloric reduction, but perhaps this concept deters true understanding of "healthful eating" and may have larger health implications for those with disordered eating.
There is a growing knowledge that that not all calories are created equal. Different foods may not only have different effects on hunger and satiety but also insulin production, gut microbiome interactions, and de novo lipogenesis in the liver (1). While not all consumers need this level of understanding, but without a basic acknowledgement of food’s qualities- like fats, fiber, sugar, ect- the consumer is lead to believe that calories are the most important determinant in what makes food “healthful.” With PACE food labeling, a consumer is led to believe that an ice cream cone and a handful of nuts, both of which could amount to 200 calories, are “equal.” However, in this comparison, only the nuts are possibly advantageous to people with diabetes and cardiovascular disease (2).
Stripping foods down to solely their caloric energy through PACE food labeling could inadvertently foster unhealthy relationships with food. As stated in the article, PACE labeling could be used to “help the public understand what a calorie means and therefore more able to decide whether the calories are ‘worth it.’” Through directing consumers to regard food as just calories to burn off through exercise, instead of fuel for a person’s body, perhaps consumers will come to regard food as punishment instead of its role as nourishment. Those who could be most affected from this way of thinking are the 30 million individuals living in the US with eating disorders (3,4). While obesity does affect more individuals than eating disorders, this is a population of individuals that should be considered when suggesting policymakers to consider implementation of this labeling system. Eating disorders are characterized by a pervasive thought pattern concerning both weight and food so implementing a labeling system that emphasizes food purging through the form of exercise can be detrimental to the mental health of these unique populations (5). Eating disorders have the highest mortality rate of any mental illness and 1 in 5 anorexia deaths are by suicide (6,7). Not only could PACE food labeling adversely affect those with eating disorders, but through fostering unhealthful relationships with food, they could potentially exacerbate the issue. On the other hand, reducing the risk and/or actual prevalence of obesity and all its related ailments, including psychological stress, is a worthy endeavor.
In conclusion, while the authors of this article review a novel and potentially helpful way to combat the growing obesity epidemic, further studies need to be done to compare PACE against current public health education programs and to investigate potential harm to those with eating disorders prior to policy making.
1) Mozaffarian, D.(2017). Foods, obesity, and diabetes—are all calories created equal?, Nutrition Reviews, Issue Suppl_1 Volume 75, Pages 19–31
2) Allen, L. (2008). Priority Areas for Research on the Intake, Composition, and Health Effects of Tree Nuts and Peanuts, The Journal of Nutrition, Volume 138, Issue 9, Pages 1763S–1765S
3) Hudson, J. I., Hiripi, E., Pope, H. G., & Kessler, R. C. (2007). The prevalence and correlates of eating disorders in the national comorbidity survey replication. Biological Psychiatry, 61(3), 348–358.
4) Le Grange, D., Swanson, S. A., Crow, S. J., & Merikangas, K. R. (2012). Eating disorder not otherwise specified presentation in the US population. International Journal of Eating Disorders, 45(5), 711-718.
5) Dell'Osso, L., Abelli, M., Carpita, B., Pini, S., Castellini, G., Carmassi, C., & Ricca, V. (2016). Historical evolution of the concept of anorexia nervosa and relationships with orthorexia nervosa, autism, and obsessive-compulsive spectrum. Neuropsychiatric disease and treatment, 12, 1651–1660.
6) Smink, F. E., van Hoeken, D., & Hoek, H. W. (2012). Epidemiology of eating disorders: Incidence, prevalence and mortality rates. Current Psychiatry Reports,14, 406-414.
7) Arcelus, J., Mitchell, A. J., Wales, J., & Nielsen, S. (2011). Mortality rates in patients with anorexia nervosa and other eating disorders: a meta-analysis of 36 studies. Archives of General Psychiatry, 68, 724-731.
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...
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 for longer and, thus, perhaps eat less (3). Therefore, PACE labelling might be too simplistic and ultimately might not be the ideal option for promoting a healthy balanced diet.
People of lower socioeconomic classes are most at risk of suffering from obesity and the subsequent health related consequences of this (4). It is these same people who are likely to have less disposable income to join gyms, buy and cook fresh, nutritious meals and are less likely to access health care. Public Health England should be focusing on making healthy foods more accessible and cheaper so that everyone has the option to incorporate foods such as fruits and vegetables into their diet.
Innovative ideas are needed to promote weight loss in the current obesity epidemic. However, more realistic steps are required to make sure that these are targeted at those who are most at risk.
References
1. Daley AJ, McGee E, Bayliss S, Coombe A and Parretti H. lEffects of physical activity calorie equivalent food labelling to reduce food selection and consumption: systematic review and meta-analysis of randomised controlled studies. J Epidemiol Community Health. Published Online First: 10 December 2019. doi: 10.1136/jech-2019-213216
2. Royal Society for Public Health. Introducing “activity equivalent” calorie labelling to tackle obesity. [Internet]. 2016. [Cited 2019 December 15]. Available from: https://www.rsph.org.uk/uploads/assets/uploaded/26deda5b-b3b7-4b15-a11be...
3. Overby NC, Sonestedt E, Laaksonen DE, Birgisdottir BE. Dietary fiber and the glycemic index: a background paper for the Nordic Nutrition Recommendations 2012. Food Nutr Res. 2013;57:10.3402/fnr.v57i0.20709. doi:10.3402/fnr.v57i0.20709
Davis and colleagues must be commended for their concern about cancer outcomes in patients with mental disorders and for acknowledging the poor quality of research.(1) However, their statement “pre-existing mental disorder have a higher odds of advanced stage cancer at diagnosis “ deserve comment.
Firstly, patients with mental disorders, as all vulnerable populations, have poor access to care, considering either quantitatively or qualitatively, even more for specialized care, whatever it could be. Accordingly, a vertical approach only targeting patients with mental disorders would only be a partial and symptomatic solution A root cause analysis is a prerequisite to expect fixing a systemic failure.
Secondly, the term “pre-existing mental disorder” must be questioned as tobacco and alcohol cause both mental health problems and cancer. There is robust and accumulating evidence that cigarette smoking is a causal risk factor for anxiety, depression and, even severe mental illness such as bipolar disorder.(2) Cessation is associated with reduced depression, anxiety and, improved quality of life. While one can understand most patients are fooled by the immediate effects of smoking on perceived stress (decreasing cerebral pain from nicotine withdrawal), the fact that too many psychiatric setting remain smokehouses question the quality of care.(3) Similarly, in many experience, as a second line specialist for severe alcohol use disorders, many of patients referred t...
Davis and colleagues must be commended for their concern about cancer outcomes in patients with mental disorders and for acknowledging the poor quality of research.(1) However, their statement “pre-existing mental disorder have a higher odds of advanced stage cancer at diagnosis “ deserve comment.
Firstly, patients with mental disorders, as all vulnerable populations, have poor access to care, considering either quantitatively or qualitatively, even more for specialized care, whatever it could be. Accordingly, a vertical approach only targeting patients with mental disorders would only be a partial and symptomatic solution A root cause analysis is a prerequisite to expect fixing a systemic failure.
Secondly, the term “pre-existing mental disorder” must be questioned as tobacco and alcohol cause both mental health problems and cancer. There is robust and accumulating evidence that cigarette smoking is a causal risk factor for anxiety, depression and, even severe mental illness such as bipolar disorder.(2) Cessation is associated with reduced depression, anxiety and, improved quality of life. While one can understand most patients are fooled by the immediate effects of smoking on perceived stress (decreasing cerebral pain from nicotine withdrawal), the fact that too many psychiatric setting remain smokehouses question the quality of care.(3) Similarly, in many experience, as a second line specialist for severe alcohol use disorders, many of patients referred to me are treated with antidepressants. Antidepressants have modest, if any, useful effects in depressed drinkers but have a potential to aggravate drinking outcomes (pathological intoxication with marked lost control and, occasionally serious violence, even suicide or homicide).(4) This is a real issue in France: a) the use of alcohol, a most depressive agent, is a public health crisis as in England; b) in contrast to England psychotherapy is not reimbursed by the French mandatory healthcare scheme yet despite the success of the Improving Access to Psychological Therapies programme launched in 2008.
Last, even if a pre-existing mental disorder can to be the main concern, as in patients with schizophrenia, no one must overlook that these patients are 3.5 times more likely to die than the general population due to lung cancer, chronic obstructive pulmonary and cardiovascular diseases. For the main psychiatric cause of death, suicide, whose prevention remains a challenge, standardized mortality ratios is 52/100,000 person-years vs 75 for lung cancer.(5) In contrast, adequate treatment for smoking cessation, psychotherapy and nicotine replacement therapy with the belt and brace strategy (patches plus oral forms to suppress occasional craving, at increasing doses) is most effective, whether there are mental health disorders or not.
1 Davis LE, Bogner E, Coburn NG et al. Stage at diagnosis and survival in patients with cancer and a pre-existing mental illness: a meta-analysis. J Epidemiol Community Health 2020;74:84-94.
2 Vermeulen JM, Wootton RE, Treur JL et al. Smoking and the risk for bipolar disorder: evidence from a bidirectional Mendelian randomisation study. Br J Psychiatry. 2019. Online Sep 17. doi: 10.1192/bjp.2019.202.
3 Evins AE, Cather C, Daumit GL. Smoking cessation in people with serious mental illness. Lancet Psychiatry2019;6:563-564.
4 Braillon A. Alcohol Use Disorders and the Barrel of the Danaids. Alcohol Alcohol 2016;51:774.
5 Gatov E, Rosella L, Chiu M, et al. Trends in standardized mortality among individuals with schizophrenia, 1993–2012: a population-based, repeated cross-sectional study. CMAJ 2017;189:E1177–87.
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...
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 study, however, also finds that after 2010 mortality among upper non-manual workers rapidly increased, causing a reversal of the upper non-manual/manual rate ratio. It is unlikely that this is due to a change in the recording of occupation. According to our information, there was a slight change in the method of recording occupation on Korean death certificates during the 1990s, but there has been no further changes since the year 2000.[5-6] Therefore, we believe that the discrepancy between some Korean studies and our results mentioned by Prof. Khang is due to a difference in study period.
Prof. Khang’s letter implicitly also suggests the possibility that numerator-denominator bias explains our findings on Japan. In contrast to South Korea, there are no longitudinal studies in Japan in which occupational class at baseline can be related to mortality during follow-up. We therefore can only speculate about the magnitude and direction of this bias. However, the method of recording occupation on death certificates or the census has not changed during the study period in Japan, and the deterioration of the mortality rate among upper non-manual workers is therefore unlikely to be an artefact.
Reference
1. Tanaka H, Nusselder WJ, Bopp M, et al. Mortality inequalities by occupational class among men in Japan, South Korea and eight European countries: a national register-based study, 1990–2015. J Epidemiol Community Health 2019;73:750-758. doi:10.1136/jech-2018-211715
2. Shkolnikov VM, Jasilionis D, Andreev EM, et al. Linked versus unlinked estimates of mortality and length of life by education and marital status: evidence from the first record linkage study in Lithuania. Soc Sci Med 2007;64:1392–406. doi:10.1016/j.socscimed.2006.11.014
3. Kim HR, Khang YH. [Reliability of education and occupational class: a comparison of health survey and death certificate data]. J Prev Med Public Health. 2005;38:443-448. (in Korean)
4. Lee H-E, Kim H-R, Chung YK, et al. Mortality rates by occupation in Korea: a nationwide, 13-year follow-up study. Occup Environ Med 2016;73:329–35. doi:10.1136/oemed-2015-103192
5. Vital Statistics Division, Social Statistics Bureau, Statistics Korea (KOSTAT) [Internet]. Available: http://kostat.go.kr/portal/eng/aboutUs/3/2/9/2/index.static (Accessed 23 Sep 2019)
6. Supreme Court of Korea. Regulation on Document Form of Family Related Registration (in Korean) [Internet]. Available: https://glaw.scourt.go.kr/wsjo/gchick/sjo330.do?contId=2258861&q=%EA%B0%... (Accessed 24 Sep 2019)
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...
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 basic needs among the common variables in EUSILC and the national census of the country concerned. Detailed construction was described previously (2)
Conversely to what Allik et al. interpretation might suggest, we have never thought of proposing to all European countries to use the French version of EDI, but proposed to each country included in EUSILC the same theory–based methodology to allow comparability while accounting for each specific context.
Even if national policies is capable to some extent to curb rising inequality, we think Europe is the most relevant level to analyze and tackle health inequalities. Thanks to the extension of the construction of trans-cultural deprivation index in a growing number of European countries (3), several studies have been carried out in recent years on different aspects of social inequalities of health in a comparative way between different European countries (4,5)
1- Allik M, Leyland A, Ichiara MYT, Dundas R. Creating small-area deprivation indices: a guide for stage and options. J Epidemiol Comm Health. 2019;0 1-6. Doi:10.1136/jech.2019-213255
2- Pornet C, Delpierre C, Dejardin O, Grosclaude P, Launay L, Guittet L,Lang T, Launoy G. Construction of an adaptable European transnational ecological deprivation index: the French version J Epidemiol Comm Health . 2012 Nov;66(11):982-9.
3- Guillaume E, Pornet C, Dejardin O, Launay L, Lillini R, Vercelli M, Marí-Dell’Olmo M, Fernández- Fontelo A, Borrell C, Ribeiro AI, Fatima de Pina M, Mayer A, Delpierre C, Rachet B, Launoy G. Development of a cross-cultural deprivation index in five European countries. J Epidemiol Comm Health 2016 May;70(5):493-9
4- Ribeiro AI, Fraga S, Kelly-Irving M, Delpierre C, Stringhini S, Kivimaki M, Joost S, Guessous I, Gandini M, Vineis P, Barros H.Neighbourhood socioeconomic deprivation and allostatic load: a multi-cohort study. Sci Rep. 2019 Jun 19;9(1):8790.
5- Robinson O, Tamayo I, de Castro M et al. The Urban Exposome during Pregnancy and Its Socioeconomic Determinants. Env Health Perspectives 2018 ; 126 ;7.
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...
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 in Korea. The percentage in Japan was even greater. Moreover, the methods of recording occupation in Korean death certificates have changed during recent decades. In the 1990s, ‘occupation before death’ was recorded, which was later changed to ‘occupation at the time of occurrence of disease or accident’. This change might have influenced the trends reported by Tanaka and colleagues [1] in mortality according to occupational class between 1990 and 2015. In fact, several national studies in Korea employing individual mortality follow-up have shown clear mortality inequalities unfavorable to manual workers compared with non-manual workers [3, 4, 5]. A recent KNHANES long-term mortality follow-up study revealed that male manual workers aged 30-64 had 3.85 times higher (95% confidence interval: 2.25–6.60) mortality risks than their non-manual counterparts [3]. In conclusion, the surprising reverse pattern in the relationship between occupational class and mortality in Korea reported by Tanaka and colleagues [1] is likely due to numerator-denominator bias, and therefore may not reflect the true situation in Korea.
1. Tanaka H, Nusselder WJ, Bopp M, Brønnum-Hansen H, Kalediene R, Lee JS, Leinsalu M, Martikainen P, Menvielle G, Kobayashi Y, Mackenbach JP. Mortality inequalities by occupational class among men in Japan, South Korea and eight European countries: a national register-based study, 1990–2015. J Epidemiol Community Health doi: 10.1136/jech-2018-211715
2. Kim HR, Khang YH. [Reliability of education and occupational class: a comparison of health survey and death certificate data]. J Prev Med Public Health. 2005;38:443-8. (in Korean)
3. Khang YH, Kim HR. Socioeconomic Inequality in mortality using 12-year follow-up data from nationally representative surveys in South Korea. Int J Equity Health 2016;15:51.
4. Khang YH, Lee SI, Lee MS, Jo MW. Socioeconomic mortality inequalities in Korea Labor & Income Panel Study. Korean J Health Policy Admin 2004;14:1-20. (in Korean)
5. Lee HE, Kim HR, Chung YK, Kang SK, Kim EA. Mortality rates by occupation in Korea: a nationwide, 13-year follow-up study. Occup Environ Med 2016;73:329-35.
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...
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 Survey 2014 only measured women for body mass index (BMI) and the most recent STEPwise surveillance was 16 years ago in Lagos state only (1, 3). Oyeyemi et al. (2018) reported major gaps in physical activity research in Nigeria (4). Overnutrition and physical activity data, in our view, should be a research priority when developing obesity prevention policy.
Thirdly, Chigbu and colleagues measured body mass index (BMI), waist circumference and tricep skinfold thickness, yet only BMI was used for obesity classification (1). BMI does not measure fat tissue percentage or where fat tissue is located, and these are both important health indicators (5). There are more accurate measures of fat mass than BMI, such as bioelectrical impedance methods (5), although these may not be appropriate for population studies in resource-constrained settings. However, waist circumference can be used with BMI as a more accurate, yet cost effective, measure of health risk (5).
Finally, although Chigbu and associates have provided valuable information, we suggest that identification of limitations in their research would be helpful especially when using information for the development of obesity prevention policy in Nigeria.
References:
1. Chigbu CO, Parhofer KG, Aniebue UU, et al. 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. J Epidemiol Community Health. 2018;72(8):702-7.
2. Kandala NB, Stranges S. Geographic variation of overweight and obesity among women in Nigeria: a case for nutritional transition in sub-Saharan Africa. PLoS One. 2014;9(6):e101103.
3. Nigerian Heart Foundation and Federal Minstry of Health and Social Services. Health Behaviour Monitor Among Nigerian Adult Popultaion. 2003 [Date accessed: March 2019]. Available from: https://www.who.int/ncds/surveillance/steps/2003_STEPS_Report_Nigeria.pdf
4. Oyeyemi AL, Oyeyemi AY, Omotara BA, et al. Physical activity profile of Nigeria: implications for research, surveillance and policy. Pan Afr Med J. 2018;30:175.
5. Nuttall FQ. Body Mass Index: Obesity, BMI, and Health: A Critical Review. Nutri Today. 2015;50(3):117-28.
We read with interest, intrigue and concern the findings reported in this short report. if the findings are validated from larger and multicentric data this may have huge implications in the way we trace and isolate the COVID-19 contacts. Pre symptomatic transmission from index cases 5 days prior to the onset of symptoms is a huge logistical nightmare in terms of containment strategies. This would imply at practical impossibility and futility of these strategy especially in setting of cluster or community transmission. This also highlights the virtues of basic but universal measures like physical distancing, hygiene and use of mask at all times under specific settings.
The question “Why does Russia have such high cardiovascular (CV) mortality rates?”1 can be answered by a pathologist who practiced during the Soviet time.2 Since then, the quality of post mortem examinations has decreased especially during the 1990s: autopsies were sometimes made perfunctorily. The deterioration in anatomic pathology and the health care in general during the 1990s coincided with the increase in the registered CV mortality. A tendency to over-diagnose CV diseases is generally known to exist also for people dying at home and not undergoing autopsy. If a cause of death is not entirely clear, it has been usual to write on a death certificate: “Ischemic heart disease with cardiac insufficiency” or a similar formulation.2 Concerning the relatively high CV mortality in Russia, it should be commented that irregular treatment of hypertension,3 diabetes and other chronic diseases continues to be a problem. Considering the above, the differences between Norwegian and Russian cohorts1 can be better understood. The levels of serum lipids were comparable between Russia and Norway being slightly higher in the latter possibly due to better nutrition. Interestingly, N-terminal pro-b-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and high-sensitivity C-reactive protein (hsCRP) were higher in Russia.1 It can be reasonably assumed that average levels of these markers inversely correlate with a nation’s health reflected by the life expecta...
Show MoreWe read with great interest the report from Hamer and colleagues that examined the hypothesis that associations between television (TV) viewing and mortality from heart disease (HD) are due to confounding (1). They employed a negative control approach (2) and report evidence of associations between TV viewing and HD mortality (HR=1.09 [1.06, 1.12] per 1 hr/day increase in TV) and accidental deaths (the negative control outcome; HR=1.06 [0.98, 1.15]) after adjusting for age, sex, smoking, education, and prevalent HD (1)
The positive association between TV and accidental deaths was interpreted as evidence that the TV-HD mortality association was due to confounding. Although key study limitations were noted including a small number of accidental deaths and limited adjustment for confounding, the authors concluded that “observed associations between TV and HD are likely to be driven by confounding”. Although we agree that confounding is a worrisome threat to the internal validity of epidemiologic studies, we believe that the conclusion in the Hamer report is overstated.
A critical additional strategy to understand bias due to confounding, one that was not employed in the current study, is to examine relevant results from published studies conducted in different study populations using different methods. (2) We previously reported results in two studies that examined associations for accidental deaths and HD mortality with TV viewing (3) and leisure-time sitti...
Show MoreDear Editor,
Show MoreThe authors of “Effects of physical activity calorie equivalent food labelling to reduce food selection and consumption: systematic review and meta-analysis of randomized controlled studies” make a strong claim that PACE food labeling can increase consumer consciousness of calorie consumption and therefore caloric reduction, but perhaps this concept deters true understanding of "healthful eating" and may have larger health implications for those with disordered eating.
There is a growing knowledge that that not all calories are created equal. Different foods may not only have different effects on hunger and satiety but also insulin production, gut microbiome interactions, and de novo lipogenesis in the liver (1). While not all consumers need this level of understanding, but without a basic acknowledgement of food’s qualities- like fats, fiber, sugar, ect- the consumer is lead to believe that calories are the most important determinant in what makes food “healthful.” With PACE food labeling, a consumer is led to believe that an ice cream cone and a handful of nuts, both of which could amount to 200 calories, are “equal.” However, in this comparison, only the nuts are possibly advantageous to people with diabetes and cardiovascular disease (2).
Stripping foods down to solely their caloric energy through PACE food labeling could inadvertently foster unhealthy relationships with food. As stated in the article, PACE labeling could be use...
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...
Show MoreDavis and colleagues must be commended for their concern about cancer outcomes in patients with mental disorders and for acknowledging the poor quality of research.(1) However, their statement “pre-existing mental disorder have a higher odds of advanced stage cancer at diagnosis “ deserve comment.
Firstly, patients with mental disorders, as all vulnerable populations, have poor access to care, considering either quantitatively or qualitatively, even more for specialized care, whatever it could be. Accordingly, a vertical approach only targeting patients with mental disorders would only be a partial and symptomatic solution A root cause analysis is a prerequisite to expect fixing a systemic failure.
Secondly, the term “pre-existing mental disorder” must be questioned as tobacco and alcohol cause both mental health problems and cancer. There is robust and accumulating evidence that cigarette smoking is a causal risk factor for anxiety, depression and, even severe mental illness such as bipolar disorder.(2) Cessation is associated with reduced depression, anxiety and, improved quality of life. While one can understand most patients are fooled by the immediate effects of smoking on perceived stress (decreasing cerebral pain from nicotine withdrawal), the fact that too many psychiatric setting remain smokehouses question the quality of care.(3) Similarly, in many experience, as a second line specialist for severe alcohol use disorders, many of patients referred t...
Show MoreAs 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.
Show MoreWhile 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...
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.
Show MoreThis 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...
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...
Show MoreDear 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...
Show MorePages