In this paper we sought to explore the idea that the delivery of health promoting interventions could be tailored in ways that might increase uptake among hard-to-reach populations, potentially helping to reduce health inequalities. In hindsight, we realise that the specific intervention used in this study was extremely inappropriate. We acknowledge that the intervention involved drew on stereotypes for female nurses, reinforced the objectification of both women and nurses, thus reinforcing gender inequalities. We also acknowledge criticism that some of the terms we used in translating our paper into English caused offense to some readers.
We are deeply sorry for our poor judgement and for the negative impacts of this paper. As health inequalities researchers, we are very concerned about the macrosocial determinants of health inequality and recognize that gender inequalities are one such determinant. While it has been very difficult for us to receive such a negative response to our paper, we are grateful to those who have helped us understand its limitations and how we can avoid these in future.
Response to Tsujimoto and Kataoka
We thank the Tsujimoto and Kataoka for their comments. While we agree that it would be helpful to formally test for gender differences in the effect of the study intervention, we are unable to conduct such an analysis since permission to use the data, as approved by the ethics board, has now expired. As we discuss in the paper...
In this paper we sought to explore the idea that the delivery of health promoting interventions could be tailored in ways that might increase uptake among hard-to-reach populations, potentially helping to reduce health inequalities. In hindsight, we realise that the specific intervention used in this study was extremely inappropriate. We acknowledge that the intervention involved drew on stereotypes for female nurses, reinforced the objectification of both women and nurses, thus reinforcing gender inequalities. We also acknowledge criticism that some of the terms we used in translating our paper into English caused offense to some readers.
We are deeply sorry for our poor judgement and for the negative impacts of this paper. As health inequalities researchers, we are very concerned about the macrosocial determinants of health inequality and recognize that gender inequalities are one such determinant. While it has been very difficult for us to receive such a negative response to our paper, we are grateful to those who have helped us understand its limitations and how we can avoid these in future.
Response to Tsujimoto and Kataoka
We thank the Tsujimoto and Kataoka for their comments. While we agree that it would be helpful to formally test for gender differences in the effect of the study intervention, we are unable to conduct such an analysis since permission to use the data, as approved by the ethics board, has now expired. As we discuss in the paper, however, the proportion of study participants in the intervention group (rather than the control group) was similar for women and men; and the association between intervention uptake and low-SES was of similar magnitude for women and men (Table 2). Thus it is possible that the higher levels of health check uptake in the intervention group are due to factors other than sexual attraction (as noted in our discussion of possible mechanisms to explain the observed association). We agree that this question warrants further investigation.
This is the second E-letter from the Editors of the Journal of Epidemiology & Community Health concerning a paper by Kondo and Ishikawa [http://jech.bmj.com/content/early/2018/01/12/jech-2017-209943]. The paper examined the impact of an intervention to encourage people of lower socio-economic status attending pachinko parlours in Japan to undergo health checkups. The intervention, which was not controlled by the authors, used gendered stereotypes of the nursing profession and suggestive uniforms that play on women’s sexuality to encourage people to engage in health checkups. The study conducted was granted ethical approval by an institutional research ethics board.
JECH condemns the use of sexism, gender and professional stereotypes and other forms of discriminatory practice or language for any purpose, including health promotion programs. The intervention studied in the article contradicts our principles. Concerns about this paper have been sent to us and we have published these as E-letters that are attached to the article.
We have conducted an audit of our review processes and determined that an improbable chain of accidental human processing errors in the online editorial system meant that we failed to give this paper the usual scrutiny and oversight our submissions receive. In our time as Editors, we have overseen more than 10,000 manuscript submissions prior to this withou...
This is the second E-letter from the Editors of the Journal of Epidemiology & Community Health concerning a paper by Kondo and Ishikawa [http://jech.bmj.com/content/early/2018/01/12/jech-2017-209943]. The paper examined the impact of an intervention to encourage people of lower socio-economic status attending pachinko parlours in Japan to undergo health checkups. The intervention, which was not controlled by the authors, used gendered stereotypes of the nursing profession and suggestive uniforms that play on women’s sexuality to encourage people to engage in health checkups. The study conducted was granted ethical approval by an institutional research ethics board.
JECH condemns the use of sexism, gender and professional stereotypes and other forms of discriminatory practice or language for any purpose, including health promotion programs. The intervention studied in the article contradicts our principles. Concerns about this paper have been sent to us and we have published these as E-letters that are attached to the article.
We have conducted an audit of our review processes and determined that an improbable chain of accidental human processing errors in the online editorial system meant that we failed to give this paper the usual scrutiny and oversight our submissions receive. In our time as Editors, we have overseen more than 10,000 manuscript submissions prior to this without incident, and we deeply regret this lapse. We have already identified how similar situations can be avoided in the future. Effective immediately, we will implement changes to our web-based submission system to add extra checks and sign-offs in the editorial process in order to avoid errors and ensure we uphold our editorial principles.
Research published in articles in JECH will inevitably study social situations where sexism, racism and other forms of discrimination, injustice and exploitation are present, but we as Editors have a responsibility to ensure that our published content names such practices and condemns them as socially unacceptable. Reporting such practices uncritically or neutrally is not acceptable, and perpetuates societal perceptions that such practices are normal and/or unproblematic. In this particular case, we failed to meet this standard, and we sincerely apologize to all of our readers for this lapse in oversight.
In addition, we are also taking this opportunity to make additional improvements to the journal. First, we will develop a statement of principles for submissions to ensure that discriminatory and/or exploitative practices are examined in a critical fashion and our articles avoid discriminatory language. Second, the Editors will write to the Institutional Research Ethics Board that gave approval for this study and make that body aware of our concerns, the concerns published in E-letters, and other concerns we have received.
We are mindful of the fact that the journal’s reputation is important to an entire community of scholars and readers, and we take that very seriously. We will use this incident as an opportunity to address not only the direct challenges of consistently attaining the highest standards for editorial handling of manuscripts, but also solidifying the values that underpin the journal and the scholarship it publishes. It has not escaped our attention that many of the voices who rightly critiqued our error also provided informed and thoughtful insights, and it is our commitment that the journal be a trusted platform for such rigorous, critical scholarship that challenges health and social inequities both locally and globally.
Barberio et al1 report a study which – in contrast to our own study2 - shows no relationship between fluoride intake and hypothyroidism. However, Barberio et al study is limited by the methods used for identifying hypothyroidism prevalence, fluoridation status and sample sizes.
Barberio et al utilised three methods to determine hypothyroidism prevalence: self-report and two biomarkers: thyroid-stimulating hormone (TSH), and free T4 blood results. This is problematic as self-report is unlikely to provide accurate prevalence data when compared to clinical diagnosis data, as used in our study4; and there are a number of studies demonstrating that self-reported estimates of thyroid functioning are unreliable. Further, the self-report question does not appear to differentiate between under and over active thyroid functioning. The biomarker data only included individuals with un-medicated hypothyroidism; consequently, the sample is unrepresentative of the population. The analysis of this data provides correlations between the biomarkers TSH, T4 readings and fluoride exposure in a sub-sample of respondents, assuming that all respondents received uniform levels of fluoride. From our data, we observed wide variability within fluoridated areas. This may explain why in table 2b, none of the variables, including age and sex, were predictive of TSH levels. This contradicts Barberio et al’s own data on what is predictive of hypothyroidism and the Canadian Health Measures Survey...
Barberio et al1 report a study which – in contrast to our own study2 - shows no relationship between fluoride intake and hypothyroidism. However, Barberio et al study is limited by the methods used for identifying hypothyroidism prevalence, fluoridation status and sample sizes.
Barberio et al utilised three methods to determine hypothyroidism prevalence: self-report and two biomarkers: thyroid-stimulating hormone (TSH), and free T4 blood results. This is problematic as self-report is unlikely to provide accurate prevalence data when compared to clinical diagnosis data, as used in our study4; and there are a number of studies demonstrating that self-reported estimates of thyroid functioning are unreliable. Further, the self-report question does not appear to differentiate between under and over active thyroid functioning. The biomarker data only included individuals with un-medicated hypothyroidism; consequently, the sample is unrepresentative of the population. The analysis of this data provides correlations between the biomarkers TSH, T4 readings and fluoride exposure in a sub-sample of respondents, assuming that all respondents received uniform levels of fluoride. From our data, we observed wide variability within fluoridated areas. This may explain why in table 2b, none of the variables, including age and sex, were predictive of TSH levels. This contradicts Barberio et al’s own data on what is predictive of hypothyroidism and the Canadian Health Measures Survey prevalence estimates for hypothyroidism. 3 Finally, The sample size for the individual level fluoride status was much smaller that the full sample and not reported fully within the paper; indeed, Statistics Canada prohibited the authors from carrying out some analyses due to ‘sample sizes requirements’. It is reasonable to estimate that no more than 15 people with hypothyroidism are likely to be included in the sample reported in table 3; this raises questions about the statistical power of this analysis.
Barberio et al suggest that the differences in findings could be – in part - due to iodine deficiency in England; however, they did not refer to the most recent data which showed that iodine intake was adequate in all age/sex groups.5 We suggest that the different classification of hypothyroidism prevalence and potential weaknesses in the statistical analysis account for the different findings of the two studies. We believe the following questions need to be answered:
1. How certain are they that participants understood they were being asked specifically about hypothyroidism when asked if they had a ‘thyroid condition’?
2. Why do they think age and sex, which are uncontentious predictors of hypothyroidism, do not provide any predictive value in the model of the biomarker TSH (presented in Table 2b)?
3. What was the statistical power for the comparisons presented in tables 3a and b?
Without further clarification of these issues, it is not possible to have confidence in the findings reported by Barberio et al, and we do not accept that their study refutes our findings. However, we do agree with Barberio et al and other commentators that more individual level analyses are required to explore the relationship between thyroid function and fluoride exposure.
References:
1. Barberio AM, Hosein FS, Quiñonez C, McLaren L. Fluoride exposure and indicators of thyroid functioning in the Canadian population: implications for community water fluoridation. J Epidemiol Community Health. 2017 Oct 1;71(10):1019-25.
2. Peckham S, Lowery D, Spencer S. Are fluoride levels in drinking water associated with hypothyroidism prevalence in England? A large observational study of GP practice data and fluoride levels in drinking water. J Epidemiol Community Health 2015;69:619–24.
3. Rotermann, M., Sanmartin, C., Hennessy, D., & Arthur, M. (2014). Prescription medication use by Canadians aged 6 to 79. Health reports, 25(6), 3.
4. Banks E, Beral V, Cameron R, Hogg A, Langley N, Barnes I, Bull D, Elliman J, Harris CL. Agreement between general practice prescription data and self-reported use of hormone replacement therapy and treatment for various illnesses. Journal of Epidemiology and Biostatistics. 2001 Jul 1;6(4):357-63.
Madureira-Lima and Galea developped an Alcohol Control Policy Index (ACPI) and claimed higher scores with their index were associated with lower consumption.(1) This deserved comment.
First, why looking for a complex and time consuming surrogate when the relevant endpoint, consumption, is so easy to assess? Moreover, if reliable data about consumption were not accessible, this would be the best indicator for lack of alcohol control policy.
Second, how France can rank in the top, 6th among 48 developed countries, for alcohol control? Indeed: a) France is among the barrels, the male population drank an average of 43g/day (female 13g) and, male regular drinkers drank 64g (women 45g).(2) b) serial laws in 2009 and 2016 were used to almost nullify the 1991 Évin law protecting people from alcohol advertising.(3,4) c) for the devastating flawed Responsibility Lansley only copied/pasted a 2006 decree (#159) issued by Bussereau, a French minister for agriculture;(5) d) France even lobbied against the Act about minimum alcohol pricing in Scotland, claiming it “would be disastrous on the balance of European trade”(6) e) the new president hired the CEO of the wine professional organization as his special advisor for agriculture (7) because alcohol is France's second biggest export sector after the aerospace industry.
Last, in my opinion no country has implemented alcohol control yet as alcohol control must be comprehensive with robust measures. Minimum alc...
Madureira-Lima and Galea developped an Alcohol Control Policy Index (ACPI) and claimed higher scores with their index were associated with lower consumption.(1) This deserved comment.
First, why looking for a complex and time consuming surrogate when the relevant endpoint, consumption, is so easy to assess? Moreover, if reliable data about consumption were not accessible, this would be the best indicator for lack of alcohol control policy.
Second, how France can rank in the top, 6th among 48 developed countries, for alcohol control? Indeed: a) France is among the barrels, the male population drank an average of 43g/day (female 13g) and, male regular drinkers drank 64g (women 45g).(2) b) serial laws in 2009 and 2016 were used to almost nullify the 1991 Évin law protecting people from alcohol advertising.(3,4) c) for the devastating flawed Responsibility Lansley only copied/pasted a 2006 decree (#159) issued by Bussereau, a French minister for agriculture;(5) d) France even lobbied against the Act about minimum alcohol pricing in Scotland, claiming it “would be disastrous on the balance of European trade”(6) e) the new president hired the CEO of the wine professional organization as his special advisor for agriculture (7) because alcohol is France's second biggest export sector after the aerospace industry.
Last, in my opinion no country has implemented alcohol control yet as alcohol control must be comprehensive with robust measures. Minimum alcohol pricing and health warnings indicating alcohol is a carcinogen are pre-requisites. Alcohol is a human carcinogen (Class 1) with dose-related increases in prevalence of cancers beginning, at the 1-2 drinks/day (10-20g). Happily, Yukon, a small territory in Canada, implemented this November mandatory labels warning of an elevated risk of cancer on alcoholic beverages.(8)
Coincidentally, reducing nicotine content and banning menthol, the most effective measures for tobacco control are not implemented even in countries targeting the tobacco endgame. However, as a skeptic I do not believe in coincidence. Could the fox be the one in charge of the henhouse?
1 Madureira-Lima J, Galea S. Alcohol control policies and alcohol consumption: an international comparison of 167 countries. J Epidemiol Community Health. 2017. Online Oct 23. doi: 10.1136/jech-2017-209350.
2 Guérin S, Laplanche A, Dunant A, Hill C. Alcohol-attributable mortality in France. Eur J Public Health. 2013;23(4):588-93.
3 Braillon A, Dubois G. Alcohol control policy: evidence-based medicine versus evidence-based marketing. Addiction 2011;106(4):852-3.
4 Gallopel-Morvan K, Spilka S, Mutatayi C, Rigaud A, Lecas F, Beck F. France's Évin Law on the control of alcohol advertising: content, effectiveness and limitations. Addiction 2017;112 (Suppl 1):86-93.
5 Braillon A. Pinnochio awards: Public Health Responsibility Deal among the nominees! Health Policy. 2017;121(1):92-93.
Stress resilience and cancer risk: a nationwide cohort study (Journal of Epidemiology and Community Health, Volume 71 Issue 10) was a real eye opener to throw light on a new arena of cancer studies. This could be a serious issue in a developing country like India, where the number of patients diagnosed with cancer is shooting up quite alarmingly[1]. The data of National Institute of Cancer Prevention and Research ( September 2017) highlights that, people living with cancer in India is estimated to be around 2.5 million, more than 7 lakh people are newly diagnosed with cancer every year and 5,56,400 people died in 2016 alone, due to this deadly disease[2]. The burden of Thyroid cancer in India has signalled the health authority as the people suffering from thyroid cancer is more than 10 million in the population of 1.324 billion[3].
Official statistics reveal that there are only about 2000 oncologists in India to treat 10 million cancer patients and the ratio of oncologists to cancer patients is about 1:5,000, whereas, the US has a ratio of about 1:100. There are only 27 Regional Cancer Centres (RCC) in India, which are funded by Central and State Governments and 300 general hospitals. These institutions with inadequate staff, amalgamated with other constraints like financial burden and supply chain challenges make the treatment of cancer even worse[4].
The escalating cost of cancer treatment in corporate hospitals have made the treatment a night mare for common...
Stress resilience and cancer risk: a nationwide cohort study (Journal of Epidemiology and Community Health, Volume 71 Issue 10) was a real eye opener to throw light on a new arena of cancer studies. This could be a serious issue in a developing country like India, where the number of patients diagnosed with cancer is shooting up quite alarmingly[1]. The data of National Institute of Cancer Prevention and Research ( September 2017) highlights that, people living with cancer in India is estimated to be around 2.5 million, more than 7 lakh people are newly diagnosed with cancer every year and 5,56,400 people died in 2016 alone, due to this deadly disease[2]. The burden of Thyroid cancer in India has signalled the health authority as the people suffering from thyroid cancer is more than 10 million in the population of 1.324 billion[3].
Official statistics reveal that there are only about 2000 oncologists in India to treat 10 million cancer patients and the ratio of oncologists to cancer patients is about 1:5,000, whereas, the US has a ratio of about 1:100. There are only 27 Regional Cancer Centres (RCC) in India, which are funded by Central and State Governments and 300 general hospitals. These institutions with inadequate staff, amalgamated with other constraints like financial burden and supply chain challenges make the treatment of cancer even worse[4].
The escalating cost of cancer treatment in corporate hospitals have made the treatment a night mare for common man in India, although the smaller segment of the society can afford it with health insurance and other health care schemes. WHO report shows around 38 million Indians suffer from stress and anxiety. There are only fewer research studies done in the area of stress and cancer in India. Ministry of Health and Family Welfare, Government of India and Indian Council of Medical Research (ICMR) should focus research studies on this road, which is still less travelled.
Biju Soman, Aswathi Raj Lathika.
This paper is a welcome addition to attempts to explain the effects of the increased deaths in 2015 and beyond. Based on a 25-year career in NHS analysis and demand forecasting may I point out that these recurring periods of higher deaths and medical admissions are always accompanied by higher delayed discharges. Observations such as the association between delayed discharges and deaths/medical admissions have, unfortunately, never been published, however, the curious association between increased deaths and medical admissions has been published. Rather than cite over 100 studies the reader is advised to go to a list of publications at http://www.hcaf.biz/2010/Publications_Full.pdf where multiple aspects of cause and effect and possible causes have been explored.
Time lags are evident, with unexplained increased deaths always lagging unexplained increased emergency admissions, and lags between males and females evident in very small area geographies. Admissions for particular diagnoses rise while others fall during these curious events. Casemix severity may well be affected.
While it is clear that austerity has only exacerbated the impact of the current event on delayed discharges, as noted by the authors, I would be reluctant to say which trends are cause and effect, and which trends arise from association rather than causation.
The clear message is that far more research is required by both...
This paper is a welcome addition to attempts to explain the effects of the increased deaths in 2015 and beyond. Based on a 25-year career in NHS analysis and demand forecasting may I point out that these recurring periods of higher deaths and medical admissions are always accompanied by higher delayed discharges. Observations such as the association between delayed discharges and deaths/medical admissions have, unfortunately, never been published, however, the curious association between increased deaths and medical admissions has been published. Rather than cite over 100 studies the reader is advised to go to a list of publications at http://www.hcaf.biz/2010/Publications_Full.pdf where multiple aspects of cause and effect and possible causes have been explored.
Time lags are evident, with unexplained increased deaths always lagging unexplained increased emergency admissions, and lags between males and females evident in very small area geographies. Admissions for particular diagnoses rise while others fall during these curious events. Casemix severity may well be affected.
While it is clear that austerity has only exacerbated the impact of the current event on delayed discharges, as noted by the authors, I would be reluctant to say which trends are cause and effect, and which trends arise from association rather than causation.
The clear message is that far more research is required by both doctors, medical researchers, epidemiologists, and geographers. Hopefully in due time, a clearer picture will emerge.
We thank Timaeus and Scott for drawing readers' attention to our interpretation(1) of their data which differs from their own(2) (rapid response 28/7/2017). We are glad to explain our thinking especially as the issues go beyond their data and to the concepts and the UK quantitative evidence. We agree that in their paper after adjustment for three socio-economic and an area of residence variables the mortality rate ratios are lower in South Asian groups than in the White group.(2) The explanation for our different interpretation is that we placed emphasis on their model adjusting mortality for age, sex and period while they emphasised the results of models further adjusting for socio-economic status and residence.(2)
Generally the ‘healthy migrant effect’ is considered as unexpected and hence a paradox because immigrant populations sometimes have better health, most usually mortality, despite their socio-economic and other disadvantages.(3, 4) It is not generally understood as an effect that arises after adjustments for socio-economic and other related factors. In Timaeus and Scott’s model 1 the rate ratios for Indian, Pakistani and Bangladeshi populations born abroad and participating in the Longitudinal Study in England and Wales are shown in their table 5 and were 0.91, 0.95 and 1.01 with the 95% confidence intervals all including the reference value of 1. In model 1, the point estimates of the rate ratios for the same ethnic groups born in the UK were simil...
We thank Timaeus and Scott for drawing readers' attention to our interpretation(1) of their data which differs from their own(2) (rapid response 28/7/2017). We are glad to explain our thinking especially as the issues go beyond their data and to the concepts and the UK quantitative evidence. We agree that in their paper after adjustment for three socio-economic and an area of residence variables the mortality rate ratios are lower in South Asian groups than in the White group.(2) The explanation for our different interpretation is that we placed emphasis on their model adjusting mortality for age, sex and period while they emphasised the results of models further adjusting for socio-economic status and residence.(2)
Generally the ‘healthy migrant effect’ is considered as unexpected and hence a paradox because immigrant populations sometimes have better health, most usually mortality, despite their socio-economic and other disadvantages.(3, 4) It is not generally understood as an effect that arises after adjustments for socio-economic and other related factors. In Timaeus and Scott’s model 1 the rate ratios for Indian, Pakistani and Bangladeshi populations born abroad and participating in the Longitudinal Study in England and Wales are shown in their table 5 and were 0.91, 0.95 and 1.01 with the 95% confidence intervals all including the reference value of 1. In model 1, the point estimates of the rate ratios for the same ethnic groups born in the UK were similar to the above for Indian (0.88) and Pakistani (0.99) populations but much lower for Bangladeshis (0.55, with wide confidence intervals).
The interpretation of results following adjustment for socio-economic variables across different ethnic groups is difficult as reflected in a literature with contrary and unexpected findings,(5, 6) stimulating conceptual and methodological explorations.(7) Timaeus and Scott have, in addition to three socio-economic variables, also included one relating to residence in Metropolitan and non-metropolitan areas. Adjustments made little difference to the rate ratio for Indians (0.88), but reduced it for Pakistani (0.78) and Bangladeshi (0.59) populations born abroad (model 2, table 5). It is not straightforward to interpret the data, especially without examining the associations between each variable and the outcome by ethnic group as Fischbacher et al explain.(7)
Given the lack of good evidence for a healthy migrant effect in South Asian/Indian Subcontinent populations in England and Wales, (5, 8-10) though it was clear cut in Scotland, (11, 12) we interpreted Timaeus and Scott's paper as providing little evidence in favour of one. An alternative interpretation that we now offer on further reflection would have been somewhat closer to the authors’ own interpretation i.e. in Indian, Pakistani and Bangladeshi populations there was little evidence of a healthy migrant effect in age and sex adjusted data though adjustment for four additional factors indicated that it may have been suppressed by unfavourable socio-economic circumstances and living in certain kinds of areas.
Variable interpretations of data are sometimes genuine and sometimes mistakes; ours is in the former category. On this theme, Timaeus and Scott stated women born in the West Africa had lower all-cause mortality than those born in England and Wales in Wild et al’s work. But the SMR was 121(9) They also said that immigrants to England and Wales from most places of origin have lower all-cause mortality than the UK born population-that is not true for many groups, particularly those from the Indian subcontinent.(5, 9, 10, 13)
Timaeus and Scott say that UK-born minority ethnic populations do not have lower mortality than UK born Whites(2) but, as shown above, for the South Asian groups the point estimates of the rate ratios were similar to those for South Asians born abroad, and in the case of Bangladeshis were considerably lower. (That the confidence intervals straddled the reference value is surely a reflection of the smaller numbers of outcomes.)
We welcome this debate, which will hopefully stimulate further work, especially on linked mortality data sets, which are producing results(1, 2, 12, 14) which are somewhat different, especially in South Asians, from those in cross-sectional analysis of unlinked mortality and population size data.(5, 9, 10, 13) The totality of the evidence merits careful examination, possibly with reanalysis for better comparison, to judge whether there is truly a healthy migrant effect in South Asians in the UK.
1. Hayes L, White M, McNally RJQ, Unwin N, Tran A, Bhopal R. Do cardiometabolic, behavioural and socioeconomic factors explain the ‘healthy migrant effect’ in the UK? Linked mortality follow-up of South Asians compared with white Europeans in the Newcastle Heart Project. Journal of Epidemiology and Community Health. 2017.
2. Scott AP, Timaeus IM. Mortality differentials 1991-2005 by self-reported ethnicity: findings from the ONS Longitudinal Study. J Epidemiol Community Health. 2013;67(9):743-50.
3. Roura M. Unravelling migrants' health paradoxes: a transdisciplinary research agenda. J Epidemiol Community Health. 2017;71(9):870-3.
4. Bhopal RS. Migration, Ethnicity, Race and Health in Multicultural Societies. 2 ed. Oxford: Oxford University Press; 2014.
5. Marmot MG, Adelstein AM, Bulusu L. Immigrant mortality in England and Wales 1970 -78. Causes of death by country of birth. London: HMSO; 1984.
6. Harding S, Balarajan R. Longitudinal study of socio-economic differences in mortality among South Asian and West Indian migrants. EthnHealth. 2001;6:121-8.
7. Fischbacher CM, Cezard G, Bhopal RS, Pearce J, Bansal N. Measures of socioeconomic position are not consistently associated with ethnic differences in cardiovascular disease in Scotland: methods from the Scottish Health and Ethnicity Linkage Study (SHELS). International Journal of Epidemiology. 2014;43(1):129-39.
8. Balarajan R, Bulusu L, Adelstein AM, Shukla V. Patterns of mortality among migrants to England and Wales from the Indian subcontinent. BMedJ. 1984;289:1185-7.
9. Wild SH, Fischbacher C, Brock A, Griffiths C, Bhopal R. Mortality from all causes and circulatory disease by country of birth in England and Wales 2001-2003. J Public Health (Oxf). 2007;29(2):191-8.
10. Balarajan R, Bulusu L. Mortality among immigrants in England and Wales, 1979 - 83. In: Britton M, editor. Mortality and Geography: A review in the mid 1980's. London: HMSO; 1990. p. 103-21.
11. Fischbacher C, Steiner M, Bhopal R, Chalmers J, Jamieson J, Knowles D, et al. Variations in all cause and cardiovascular mortality by country of birth in Scotland, 1997-2003. Scottish Medical Journal. 2007;52(4):5-10.
12. Gruer L, Cezard G, Clark E, Douglas A, Steiner M, Millard A, et al. Life expectancy of different ethnic groups using death records linked to population census data for 4.62 million people in Scotland. Journal of Epidemiology and Community Health. 2016;70:1251-4.
13. Wild S, McKeigue P. Cross sectional analysis of mortality by country of birth in England and Wales, 1970-92. BMJ. 1997;314(7082):705-10.
14. Wallace M, Hill K. Mortality Among Immigrants in England and Wales: A Longitudinal Study. 2014.
To the Editor:
Jackson et al (1) demonstrate that head injuries sustained from 0 to 7 years predict higher rates of arrest and conduct problems in young adults. We would like to highlight however, that their findings suggest that head injury of a certain type is specifically linked to juvenile offence.
A careful examination of their work reveals a trend towards very early occurrence of head trauma that results in serious brain damage. The severity and age distribution of their dataset do not match those reported on overall (i.e. accidental and not accidental) pediatric head trauma. The British national enquiry (2) on overall pediatric head injury reports that 19% of injured children were younger than a year and that 21% of them had a Glasgow score below 15. Conversely, Jackson et al (1) show that 31% of head traumas occurred in the first year of life and that 38% of them resulted in loss of consciousness. An abundance of literature shows that, compared to children with accidental head trauma, abused children are more often < 1 year of age and hospitalized longer (3). Serious pediatric head injury in very young children is caused by inflicted trauma in a substantial number of cases. Brain hemorrhages are also markedly more common in abusive head injuries; this complication has been reported in 8-10% of children in the accident group (4), meanwhile Jackson et al (1) report the same in 18% of their subjects. Taken together, these data point at a large number...
To the Editor:
Jackson et al (1) demonstrate that head injuries sustained from 0 to 7 years predict higher rates of arrest and conduct problems in young adults. We would like to highlight however, that their findings suggest that head injury of a certain type is specifically linked to juvenile offence.
A careful examination of their work reveals a trend towards very early occurrence of head trauma that results in serious brain damage. The severity and age distribution of their dataset do not match those reported on overall (i.e. accidental and not accidental) pediatric head trauma. The British national enquiry (2) on overall pediatric head injury reports that 19% of injured children were younger than a year and that 21% of them had a Glasgow score below 15. Conversely, Jackson et al (1) show that 31% of head traumas occurred in the first year of life and that 38% of them resulted in loss of consciousness. An abundance of literature shows that, compared to children with accidental head trauma, abused children are more often < 1 year of age and hospitalized longer (3). Serious pediatric head injury in very young children is caused by inflicted trauma in a substantial number of cases. Brain hemorrhages are also markedly more common in abusive head injuries; this complication has been reported in 8-10% of children in the accident group (4), meanwhile Jackson et al (1) report the same in 18% of their subjects. Taken together, these data point at a large number of inflicted head injury within the sample of Jackson et al. In addition, much of the literature on the sequelae of early abuse shows that individuals who had been maltreated as children are at greater risk for being arrested as juveniles (5). Therefore, we would like to suggest that the well known mechanism that “violence begets violence” is worth to be taken into account for the proven association between pediatric head trauma and later violent delinquency.
REFERENCE
1. Jackson TL, Braun JM, Mello M, et al. The relationship between early childhood head injury and later life criminal behaviour: a longitudinal study. J Epidemiol Community Health 2017;71:800-5. doi: 10.1136/jech-2016-208582.
2. Trefan L, Houston R, Pearson G, et al. Epidemiology of children with head injury: a national overview. Arch Dis Child 2016;101:527-32. doi: 10.1136/archdischild-2015-308424.
3. Niederkrotenthaler T, Xu L, Parks Se, et al. Descriptive factors of abusive head trauma in young children--United States, 2000-2009. Child Abuse Negl 2013;37:446-55.doi: 10.1016/j.chiabu.2013.02.002.
4. Reece M, Sege R. Childhood head injuries: accidental or inflicted? Arch Pediatr Adolesc Med 2000;154:11-15.
5. Lansford JE, Miller-Johnson S, Berlin LJ, et al. Early physical abuse and later violent delinquency: a prospective longitudinal study. Child Maltreat 2007;12:233-45.
Hayes et al. [1] repeatedly cite a 2013 article by Scott and Timæus [2], also published in this journal, as having ‘not found a healthy migrant effect in South Asians’ and as providing ‘little evidence of a South Asian mortality advantage’. This contradicts our own interpretation of the results that we presented in that paper. We concluded that ‘Immigrants are selected for good health’. Moreover, with specific reference to South Asians, we stated that: ‘adjusted for SES and residence, … Indian, Pakistani, [and] Bangladeshi … immigrants all had lower mortality than UK-born Whites who were living in similar circumstances to them … This suggests that immigrants from the Indian subcontinent … are … selected for health’.
We think it regrettable that Hayes et al. do not indicate to readers of their paper that their interpretation of the results in our paper is almost diametrically opposed to our own. Moreover, they provide no explanation whatsoever of why they came to the view that we had misinterpreted our results.
Our study investigated all-cause mortality at ages 1−79 in 1991−2005 by self-reported ethnicity and country of birth. The data were from the Office for National Statistics Longitudinal Study of England and Wales for the cohort aged 0−64 in 1991. Poisson regression was used to adjust the estimates for metropolitan residence and three indicators of socioeconomic status. In the fully-adjusted model, but not the model that adjusted only for age, sex and per...
Hayes et al. [1] repeatedly cite a 2013 article by Scott and Timæus [2], also published in this journal, as having ‘not found a healthy migrant effect in South Asians’ and as providing ‘little evidence of a South Asian mortality advantage’. This contradicts our own interpretation of the results that we presented in that paper. We concluded that ‘Immigrants are selected for good health’. Moreover, with specific reference to South Asians, we stated that: ‘adjusted for SES and residence, … Indian, Pakistani, [and] Bangladeshi … immigrants all had lower mortality than UK-born Whites who were living in similar circumstances to them … This suggests that immigrants from the Indian subcontinent … are … selected for health’.
We think it regrettable that Hayes et al. do not indicate to readers of their paper that their interpretation of the results in our paper is almost diametrically opposed to our own. Moreover, they provide no explanation whatsoever of why they came to the view that we had misinterpreted our results.
Our study investigated all-cause mortality at ages 1−79 in 1991−2005 by self-reported ethnicity and country of birth. The data were from the Office for National Statistics Longitudinal Study of England and Wales for the cohort aged 0−64 in 1991. Poisson regression was used to adjust the estimates for metropolitan residence and three indicators of socioeconomic status. In the fully-adjusted model, but not the model that adjusted only for age, sex and period, immigrants of every ethnicity other than African and other non-Caribbean Black immigrants had significantly lower mortality than the UK-born White population. Most of our estimates of mortality by ethnic group in the UK-born population had wide confidence intervals. However, the UK-born Black Caribbean population had significantly higher mortality than the White population when we adjusted only for age, sex and period. This association disappeared after we also adjusted for socioeconomic status and place of residence.
Our own interpretation of these results remains that they demonstrate that immigrants to England and Wales, including those from South Asia, are selected for good health. However, the potential reduction in mortality arising from this healthy migrant effect is largely offset by the adverse consequences of the low socioeconomic status of most immigrants compared with the population as a whole (and equally vice versa). Our results provide no evidence to suggest that selection for health in one generation results in a persistent benefit to the mortality of subsequent generations.
References
[1] Hayes L, White M, McNally RJQ, et al. Do cardiometabolic, behavioural and socioeconomic factors explain the ‘healthy migrant effect’ in the UK? Linked mortality follow-up of South Asians compared with white Europeans in the Newcastle Heart Project. Journal of Epidemiology and Community Health 2017. doi:10.1136/jech-2017-209348
[2] Scott AP, Timæus IM. Mortality differentials 1991-2005 by self-reported ethnicity: findings from the ONS Longitudinal Study. Journal of Epidemiology and Community Health 2013; 67:743-50. doi:10.1136/jech-2012-202265
This paper makes a number of claims about health in the North relative to the South of England using comparisons of relatively low death rates. When the denominator in such calculations is a very low rate of death, the size of the difference can appear large. However, if we compare the absolute risk of dying, it is relatively close in the North and South and if we were to divide the rate of survival in the South by the rate of survival in the North each year, we would have a very small comparative statistic.
Abstracts and conclusions can easily be taken out of context and authors of papers like this one should be careful to present appropriate information. For example, the conclusion "...1.2 million northern excess deaths under age 75 over five decades.." implies very high potential death rates, a million! But this figure is presented with no population and reflects experience over 50 years. If we divide by 50, we get 24,000 deaths a year. A further weakness is that no measure of population is provided to put this total number of deaths in context. Using a plausible estimate of 20 million, for example, implies excess deaths at a rate of about 1.2 per 1,000 people. I wonder how many residents of the North are planning to migrate South today to reduce their risk of an early death by just over 1 in 1,000. Yes we should be concerned about all differences in health across regions and social groups but by inflating them with misleading divisions of one small num...
This paper makes a number of claims about health in the North relative to the South of England using comparisons of relatively low death rates. When the denominator in such calculations is a very low rate of death, the size of the difference can appear large. However, if we compare the absolute risk of dying, it is relatively close in the North and South and if we were to divide the rate of survival in the South by the rate of survival in the North each year, we would have a very small comparative statistic.
Abstracts and conclusions can easily be taken out of context and authors of papers like this one should be careful to present appropriate information. For example, the conclusion "...1.2 million northern excess deaths under age 75 over five decades.." implies very high potential death rates, a million! But this figure is presented with no population and reflects experience over 50 years. If we divide by 50, we get 24,000 deaths a year. A further weakness is that no measure of population is provided to put this total number of deaths in context. Using a plausible estimate of 20 million, for example, implies excess deaths at a rate of about 1.2 per 1,000 people. I wonder how many residents of the North are planning to migrate South today to reduce their risk of an early death by just over 1 in 1,000. Yes we should be concerned about all differences in health across regions and social groups but by inflating them with misleading divisions of one small number by another, researchers are contributing to the sensationalisation of such differences.
The paper citation is Buchan IE, et al.,North-South disparities in English mortality 1965– 2015: longitudinal population study, J Epidemiol Community Health 2017;0:1–9. doi:10.1136/jech-2017-20919
In this paper we sought to explore the idea that the delivery of health promoting interventions could be tailored in ways that might increase uptake among hard-to-reach populations, potentially helping to reduce health inequalities. In hindsight, we realise that the specific intervention used in this study was extremely inappropriate. We acknowledge that the intervention involved drew on stereotypes for female nurses, reinforced the objectification of both women and nurses, thus reinforcing gender inequalities. We also acknowledge criticism that some of the terms we used in translating our paper into English caused offense to some readers.
We are deeply sorry for our poor judgement and for the negative impacts of this paper. As health inequalities researchers, we are very concerned about the macrosocial determinants of health inequality and recognize that gender inequalities are one such determinant. While it has been very difficult for us to receive such a negative response to our paper, we are grateful to those who have helped us understand its limitations and how we can avoid these in future.
Response to Tsujimoto and Kataoka
Show MoreWe thank the Tsujimoto and Kataoka for their comments. While we agree that it would be helpful to formally test for gender differences in the effect of the study intervention, we are unable to conduct such an analysis since permission to use the data, as approved by the ethics board, has now expired. As we discuss in the paper...
This is the second E-letter from the Editors of the Journal of Epidemiology & Community Health concerning a paper by Kondo and Ishikawa [http://jech.bmj.com/content/early/2018/01/12/jech-2017-209943]. The paper examined the impact of an intervention to encourage people of lower socio-economic status attending pachinko parlours in Japan to undergo health checkups. The intervention, which was not controlled by the authors, used gendered stereotypes of the nursing profession and suggestive uniforms that play on women’s sexuality to encourage people to engage in health checkups. The study conducted was granted ethical approval by an institutional research ethics board.
JECH condemns the use of sexism, gender and professional stereotypes and other forms of discriminatory practice or language for any purpose, including health promotion programs. The intervention studied in the article contradicts our principles. Concerns about this paper have been sent to us and we have published these as E-letters that are attached to the article.
We have conducted an audit of our review processes and determined that an improbable chain of accidental human processing errors in the online editorial system meant that we failed to give this paper the usual scrutiny and oversight our submissions receive. In our time as Editors, we have overseen more than 10,000 manuscript submissions prior to this withou...
Show MoreBarberio et al1 report a study which – in contrast to our own study2 - shows no relationship between fluoride intake and hypothyroidism. However, Barberio et al study is limited by the methods used for identifying hypothyroidism prevalence, fluoridation status and sample sizes.
Barberio et al utilised three methods to determine hypothyroidism prevalence: self-report and two biomarkers: thyroid-stimulating hormone (TSH), and free T4 blood results. This is problematic as self-report is unlikely to provide accurate prevalence data when compared to clinical diagnosis data, as used in our study4; and there are a number of studies demonstrating that self-reported estimates of thyroid functioning are unreliable. Further, the self-report question does not appear to differentiate between under and over active thyroid functioning. The biomarker data only included individuals with un-medicated hypothyroidism; consequently, the sample is unrepresentative of the population. The analysis of this data provides correlations between the biomarkers TSH, T4 readings and fluoride exposure in a sub-sample of respondents, assuming that all respondents received uniform levels of fluoride. From our data, we observed wide variability within fluoridated areas. This may explain why in table 2b, none of the variables, including age and sex, were predictive of TSH levels. This contradicts Barberio et al’s own data on what is predictive of hypothyroidism and the Canadian Health Measures Survey...
Show MoreMadureira-Lima and Galea developped an Alcohol Control Policy Index (ACPI) and claimed higher scores with their index were associated with lower consumption.(1) This deserved comment.
First, why looking for a complex and time consuming surrogate when the relevant endpoint, consumption, is so easy to assess? Moreover, if reliable data about consumption were not accessible, this would be the best indicator for lack of alcohol control policy.
Second, how France can rank in the top, 6th among 48 developed countries, for alcohol control? Indeed: a) France is among the barrels, the male population drank an average of 43g/day (female 13g) and, male regular drinkers drank 64g (women 45g).(2) b) serial laws in 2009 and 2016 were used to almost nullify the 1991 Évin law protecting people from alcohol advertising.(3,4) c) for the devastating flawed Responsibility Lansley only copied/pasted a 2006 decree (#159) issued by Bussereau, a French minister for agriculture;(5) d) France even lobbied against the Act about minimum alcohol pricing in Scotland, claiming it “would be disastrous on the balance of European trade”(6) e) the new president hired the CEO of the wine professional organization as his special advisor for agriculture (7) because alcohol is France's second biggest export sector after the aerospace industry.
Last, in my opinion no country has implemented alcohol control yet as alcohol control must be comprehensive with robust measures. Minimum alc...
Show MoreStress resilience and cancer risk: a nationwide cohort study (Journal of Epidemiology and Community Health, Volume 71 Issue 10) was a real eye opener to throw light on a new arena of cancer studies. This could be a serious issue in a developing country like India, where the number of patients diagnosed with cancer is shooting up quite alarmingly[1]. The data of National Institute of Cancer Prevention and Research ( September 2017) highlights that, people living with cancer in India is estimated to be around 2.5 million, more than 7 lakh people are newly diagnosed with cancer every year and 5,56,400 people died in 2016 alone, due to this deadly disease[2]. The burden of Thyroid cancer in India has signalled the health authority as the people suffering from thyroid cancer is more than 10 million in the population of 1.324 billion[3].
Show MoreOfficial statistics reveal that there are only about 2000 oncologists in India to treat 10 million cancer patients and the ratio of oncologists to cancer patients is about 1:5,000, whereas, the US has a ratio of about 1:100. There are only 27 Regional Cancer Centres (RCC) in India, which are funded by Central and State Governments and 300 general hospitals. These institutions with inadequate staff, amalgamated with other constraints like financial burden and supply chain challenges make the treatment of cancer even worse[4].
The escalating cost of cancer treatment in corporate hospitals have made the treatment a night mare for common...
This paper is a welcome addition to attempts to explain the effects of the increased deaths in 2015 and beyond. Based on a 25-year career in NHS analysis and demand forecasting may I point out that these recurring periods of higher deaths and medical admissions are always accompanied by higher delayed discharges. Observations such as the association between delayed discharges and deaths/medical admissions have, unfortunately, never been published, however, the curious association between increased deaths and medical admissions has been published. Rather than cite over 100 studies the reader is advised to go to a list of publications at http://www.hcaf.biz/2010/Publications_Full.pdf where multiple aspects of cause and effect and possible causes have been explored.
Time lags are evident, with unexplained increased deaths always lagging unexplained increased emergency admissions, and lags between males and females evident in very small area geographies. Admissions for particular diagnoses rise while others fall during these curious events. Casemix severity may well be affected.
While it is clear that austerity has only exacerbated the impact of the current event on delayed discharges, as noted by the authors, I would be reluctant to say which trends are cause and effect, and which trends arise from association rather than causation.
The clear message is that far more research is required by both...
Show MoreWe thank Timaeus and Scott for drawing readers' attention to our interpretation(1) of their data which differs from their own(2) (rapid response 28/7/2017). We are glad to explain our thinking especially as the issues go beyond their data and to the concepts and the UK quantitative evidence. We agree that in their paper after adjustment for three socio-economic and an area of residence variables the mortality rate ratios are lower in South Asian groups than in the White group.(2) The explanation for our different interpretation is that we placed emphasis on their model adjusting mortality for age, sex and period while they emphasised the results of models further adjusting for socio-economic status and residence.(2)
Generally the ‘healthy migrant effect’ is considered as unexpected and hence a paradox because immigrant populations sometimes have better health, most usually mortality, despite their socio-economic and other disadvantages.(3, 4) It is not generally understood as an effect that arises after adjustments for socio-economic and other related factors. In Timaeus and Scott’s model 1 the rate ratios for Indian, Pakistani and Bangladeshi populations born abroad and participating in the Longitudinal Study in England and Wales are shown in their table 5 and were 0.91, 0.95 and 1.01 with the 95% confidence intervals all including the reference value of 1. In model 1, the point estimates of the rate ratios for the same ethnic groups born in the UK were simil...
Show MoreTo the Editor:
Show MoreJackson et al (1) demonstrate that head injuries sustained from 0 to 7 years predict higher rates of arrest and conduct problems in young adults. We would like to highlight however, that their findings suggest that head injury of a certain type is specifically linked to juvenile offence.
A careful examination of their work reveals a trend towards very early occurrence of head trauma that results in serious brain damage. The severity and age distribution of their dataset do not match those reported on overall (i.e. accidental and not accidental) pediatric head trauma. The British national enquiry (2) on overall pediatric head injury reports that 19% of injured children were younger than a year and that 21% of them had a Glasgow score below 15. Conversely, Jackson et al (1) show that 31% of head traumas occurred in the first year of life and that 38% of them resulted in loss of consciousness. An abundance of literature shows that, compared to children with accidental head trauma, abused children are more often < 1 year of age and hospitalized longer (3). Serious pediatric head injury in very young children is caused by inflicted trauma in a substantial number of cases. Brain hemorrhages are also markedly more common in abusive head injuries; this complication has been reported in 8-10% of children in the accident group (4), meanwhile Jackson et al (1) report the same in 18% of their subjects. Taken together, these data point at a large number...
Hayes et al. [1] repeatedly cite a 2013 article by Scott and Timæus [2], also published in this journal, as having ‘not found a healthy migrant effect in South Asians’ and as providing ‘little evidence of a South Asian mortality advantage’. This contradicts our own interpretation of the results that we presented in that paper. We concluded that ‘Immigrants are selected for good health’. Moreover, with specific reference to South Asians, we stated that: ‘adjusted for SES and residence, … Indian, Pakistani, [and] Bangladeshi … immigrants all had lower mortality than UK-born Whites who were living in similar circumstances to them … This suggests that immigrants from the Indian subcontinent … are … selected for health’.
We think it regrettable that Hayes et al. do not indicate to readers of their paper that their interpretation of the results in our paper is almost diametrically opposed to our own. Moreover, they provide no explanation whatsoever of why they came to the view that we had misinterpreted our results.
Our study investigated all-cause mortality at ages 1−79 in 1991−2005 by self-reported ethnicity and country of birth. The data were from the Office for National Statistics Longitudinal Study of England and Wales for the cohort aged 0−64 in 1991. Poisson regression was used to adjust the estimates for metropolitan residence and three indicators of socioeconomic status. In the fully-adjusted model, but not the model that adjusted only for age, sex and per...
Show MoreThis paper makes a number of claims about health in the North relative to the South of England using comparisons of relatively low death rates. When the denominator in such calculations is a very low rate of death, the size of the difference can appear large. However, if we compare the absolute risk of dying, it is relatively close in the North and South and if we were to divide the rate of survival in the South by the rate of survival in the North each year, we would have a very small comparative statistic.
Abstracts and conclusions can easily be taken out of context and authors of papers like this one should be careful to present appropriate information. For example, the conclusion "...1.2 million northern excess deaths under age 75 over five decades.." implies very high potential death rates, a million! But this figure is presented with no population and reflects experience over 50 years. If we divide by 50, we get 24,000 deaths a year. A further weakness is that no measure of population is provided to put this total number of deaths in context. Using a plausible estimate of 20 million, for example, implies excess deaths at a rate of about 1.2 per 1,000 people. I wonder how many residents of the North are planning to migrate South today to reduce their risk of an early death by just over 1 in 1,000. Yes we should be concerned about all differences in health across regions and social groups but by inflating them with misleading divisions of one small num...
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