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
This is an excellent article which serves to highlight the value of Public Health work in economic terms. The findings need to be taken into account as future health and social care systems evolve. For example, in the UK, Sustainability & Transformation Plans (STPs) will only truly be sustainable if they get past paying lip service to Public Health programmes and actually invest in their implementation.
One aspect of the paper that is less helpful, however, is the distinction between 'local' and 'national' Public Health programmes. Such a distinction is arguably unclear and invalid given the fact that many national programmes require effective local implementation in order to be effective. This local implementation includes local investment, local co-design of delivery and local promotion and engagement of stakeholders and residents. In the UK, this work is undertaken by Public Health teams in local authorities in partnership with Clinical Commissioning Groups, Primary Care teams, Pharmacists and the Voluntary Sector. Effective local implementation also relies to some degree on co-design with residents.
To take an example from the list of 'National' interventions, family planning programmes in the UK are usually funded from the local Public Health budget and implemented according to a local strategy. For example, in some areas universal provision is supplemented by outreach services aimed at offering vulnerable women...
This is an excellent article which serves to highlight the value of Public Health work in economic terms. The findings need to be taken into account as future health and social care systems evolve. For example, in the UK, Sustainability & Transformation Plans (STPs) will only truly be sustainable if they get past paying lip service to Public Health programmes and actually invest in their implementation.
One aspect of the paper that is less helpful, however, is the distinction between 'local' and 'national' Public Health programmes. Such a distinction is arguably unclear and invalid given the fact that many national programmes require effective local implementation in order to be effective. This local implementation includes local investment, local co-design of delivery and local promotion and engagement of stakeholders and residents. In the UK, this work is undertaken by Public Health teams in local authorities in partnership with Clinical Commissioning Groups, Primary Care teams, Pharmacists and the Voluntary Sector. Effective local implementation also relies to some degree on co-design with residents.
To take an example from the list of 'National' interventions, family planning programmes in the UK are usually funded from the local Public Health budget and implemented according to a local strategy. For example, in some areas universal provision is supplemented by outreach services aimed at offering vulnerable women long acting contraception that enables them to take more control over their family planning. Another example is childhood vaccination, which while delivered according to a national schedule, relies on local work with schools and primary care to maximise uptake.
Public Health is cost effective. However, we mustn't make the mistake of thinking that nationwide 'one size fits all' programmes can fulfill its potential. Our population's appetite for being 'done unto' is waning fast - and we need to get back to recognising the role of co-design and implementation at a local community level if we are to sustain enthusiasm for Public Health work.
Sirs,
Peckham et al's selective reporting of the findings of the SCHER report
(2011) risks giving readers of your journal a highly misleading
interpretation of data on the fluoride intake of children in areas
supplied with water containing 1 mg/l of fluoride.
Careful analysis of the full detail of the SCHER report (2011) shows
that 6 to 12 year olds will not exceed the recommended upper limit (UL) of
2.5 mg per...
Sirs,
Peckham et al's selective reporting of the findings of the SCHER report
(2011) risks giving readers of your journal a highly misleading
interpretation of data on the fluoride intake of children in areas
supplied with water containing 1 mg/l of fluoride.
Careful analysis of the full detail of the SCHER report (2011) shows
that 6 to 12 year olds will not exceed the recommended upper limit (UL) of
2.5 mg per day even if they are routinely taking fluoride supplements (as
tablets, drops or lozenges), swallowing 10% of their toothpaste, and
consuming around two or three times as much water per day as the European
Food Safety Authority (EFSA) estimates to be likely. It also shows that 1
to 6 year olds are very unlikely to exceed the recommended UL of 1.5 mg of
fluoride per day unless they are routinely taking fluoride supplements,
swallowing around 40% of their toothpaste and possibly also putting more
than the recommended amount of paste on their brush.
SCHER's estimates were based on figures provided by EFSA which, in
its earlier 2005 report, states: "Children aged 1-8 years have fluoride
intakes from food and water well below the UL provided the fluoride
content of their
drinking water is not higher than 1.0 mg/l." It also states: "For
children older than eight years and adults the probability of exceeding
the UL on a normal diet is estimated to be low. However, consumption of
water with a high fluoride content, e.g., more than 2-3 mg/l, predisposes
to exceeding the UL."
The target level in fluoridation schemes in England is 1 mg/l.
The above suggests that Peckham et al have not correctly represented
what SCHER was saying in the body of its report. Further, it should be
borne in mind that medical and dental practitioners in England do not
prescribe fluoride supplements to children in fluoridated areas and that
parents are advised to supervise their children's toothbrushing up to
about the age of seven - in both fluoridated and non-fluoridated areas -
to ensure that they put only a pea-sized amount of toothpaste on the brush
and they do not swallow any after they have finished brushing.
Finally, in the specific context of the Peckham et al hypothesis on
hypothyroidism, it is worth noting SCHER's conclusion that "a systematic
evaluation of human studies does not suggest a potential thyroid effect at
realistic human exposures to fluoride."
Yours sincerely,
Michael A Lennon OBE
Professor Emeritus
University of Sheffield
Dr John F Beal MBE
Hon Senior Lecturer in Dental Public Health
University of Leeds
Conflict of Interest:
Dr John Beal - Vice Chair, British Fluoridation
Prof Michael Lennon - Scientific Advisor, British Fluoridation Society
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...
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...
Show MoreThis is an excellent article which serves to highlight the value of Public Health work in economic terms. The findings need to be taken into account as future health and social care systems evolve. For example, in the UK, Sustainability & Transformation Plans (STPs) will only truly be sustainable if they get past paying lip service to Public Health programmes and actually invest in their implementation.
One aspect of the paper that is less helpful, however, is the distinction between 'local' and 'national' Public Health programmes. Such a distinction is arguably unclear and invalid given the fact that many national programmes require effective local implementation in order to be effective. This local implementation includes local investment, local co-design of delivery and local promotion and engagement of stakeholders and residents. In the UK, this work is undertaken by Public Health teams in local authorities in partnership with Clinical Commissioning Groups, Primary Care teams, Pharmacists and the Voluntary Sector. Effective local implementation also relies to some degree on co-design with residents.
To take an example from the list of 'National' interventions, family planning programmes in the UK are usually funded from the local Public Health budget and implemented according to a local strategy. For example, in some areas universal provision is supplemented by outreach services aimed at offering vulnerable women...
Show MoreSirs, Peckham et al's selective reporting of the findings of the SCHER report (2011) risks giving readers of your journal a highly misleading interpretation of data on the fluoride intake of children in areas supplied with water containing 1 mg/l of fluoride.
Careful analysis of the full detail of the SCHER report (2011) shows that 6 to 12 year olds will not exceed the recommended upper limit (UL) of 2.5 mg per...
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