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| |publishingyear=2018 | | |publishingyear=2019 |
| |authors=Jouni T. Tuomisto, Arja Asikainen, Päivi Meriläinen, Päivi Haapasaari}} | | |authors=Jouni T. Tuomisto, Arja Asikainen, Päivi Meriläinen, Päivi Haapasaari}} |
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| '''Health effects of Baltic herring and salmon: a benefit-risk assessment''' is a research manuscript about the [[Goherr assessment]] performed on the BONUS GOHERR project between 2015-2018. The manuscript is to be submitted to BMC Public Health [https://bmcpublichealth.biomedcentral.com/submission-guidelines/preparing-your-manuscript/research-article]. | | '''Health effects of nutrients and environmental pollutants in Baltic herring and salmon: a quantitative benefit-risk assessment''' is a research manuscript about the [[Goherr assessment]] performed on the BONUS GOHERR project between 2015-2018. The manuscript was submitted to BMC Public Health [https://bmcpublichealth.biomedcentral.com/submission-guidelines/preparing-your-manuscript/research-article]. Thank you for your interest. |
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| == Title page ==
| | * [https://www.livsmedelsverket.se/om-oss/press/nyheter/pressmeddelanden/efsa-skarper-bedomningen-av-dioxiner-och-pcb Swedish Food Safety Authority about EFSA dioxin assessment] |
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| * Title: Health effects of Baltic herring and salmon: a benefit-risk assessment
| | Changes to the revision 2019-09-24: |
| * Authors:
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| *: Jouni T. Tuomisto, jouni.tuomisto[]thl.fi, (corresponding author), National Institute for Health and Welfare, Kuopio, Finland.
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| *: Arja Asikainen, arja.asikainen[]thl.fi, National Institute for Health and Welfare, Kuopio, Finland.
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| *: Päivi Meriläinen, paivi.merilainen@thl.fi, National Institute for Health and Welfare, Kuopio, Finland.
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| *: Päivi Haapasaari, paivi.haapasaari[]helsinki.fi, University of Helsinki, Finland.
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| == Abstract ==
| | In addition to the analysis presented in this paper, the survey was conducted for the purpose of a consumer perception and consumption study[11] and therefore only part of the survey results are presented in this paper. |
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| '''Background:''' Dioxin health risks from fish remains a complex policy issue, because especially Baltic fish contains relatively high concentrations of pollutants although it is otherwise healthy food. We studied the health benefits and risks of Baltic herring and salmon in four countries to identify critical uncertainties and facilitate evidence-based discussion on dioxin and fish policy.
| | → The survey was designed and conducted for the purposes of this study and another study about consumer perception and consumption. The latter study[11] was published first, and it contains a more detailed description of the study methods, including the questionnaire. |
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| '''Methods:''' We performed an online survey about consumers' fish consumption and motivation in Denmark, Estonia, Finland, and Sweden. Dioxin concentrations were estimated based on a Finnish EU Fish 2 study and methylmercury concentrations from data from the Finnish Food Safety Authority. Exposure-response functions about several health endpoints were evaluated and quantified based on scientific literature. We also quantified infertility risk of men based on a recent European risk assessment of childhood dioxin exposure on sperm concentration later in life.
| | Due to these reasons and according to the national guidelines, there was no need for ethical approval[65]. |
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| '''Results:''' Baltic herring and salmon contain omega-3 fatty acids, and their beneficial impact on cardiovascular risk clearly outweighs any risks of dioxins and methylmercury especially in people more than 45 years of age, but also in young men. The critical population subgroup is young women, who may expose their children to pollutants during pregnancy and breast feeding. However, even in this group the health risks are smaller or similar than health benefits. Value of information analysis demonstrated that the remaining scientific uncertainties are not large. In contrast, there are several critical uncertainties that are valuations by nature, such as whether Baltic fish should be seen as primary or secondary source of nutrients; whether exceedance of tolerable weekly intake is an adverse outcome as such; and whether subgroup-specific restrictions are problematic or not.
| | → Due to these reasons and according to the national guidelines, there was no need for ethical approval. (National Advisory Board of Research Ethics. Ethical principles of research in the humanities and social and behavioural sciences and proposals for ethical review. Helsinki; 2009. https://www.tenk.fi/sites/tenk.fi/files/ethicalprinciples.pdf. Accessed 24 Sept 2019.) |
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| '''Conclusions:''' Potential health risks from Baltic fish have decreased to less than a half in ten years. The new EFSA risk assessment clearly increases the fraction of population exceeding the tolerable dioxin intake, but the estimates of net health impacts change only marginally. Increased use of small herring (with less pollutants) is a no-regret option. Further value-based policy discussion rather than research is needed to clarify useful actions related to dioxins in fish.
| | 22. Huan Yang, Pengcheng Xun, Ka He. Fish and Fish Oil Intake in Relation to Risk of Asthma: A Systematic Review and Meta-Analysis. PLOS November 12, 2013. https://doi.org/10.1371/journal.pone.0080048 |
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| == Keywords ==
| | 22. Yang H, Xun P, He K (2013) Fish and Fish Oil Intake in Relation to Risk of Asthma: A Systematic Review and Meta-Analysis. PLOS ONE 8(11): e80048. https://doi.org/10.1371/journal.pone.0080048 |
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| Fish consumption, dioxins, methylmercury, benefit-risk assessment, health impact, sperm concentration, Baltic Sea, knowledge crystal, food recommendation, European Food Safety Authority EFSA.
| | 23. Asmaa S Abdelhamid, Tracey J Brown, Julii S Brainard, Priti Biswas, Gabrielle C Thorpe, Helen J Moore, Katherine HO Deane, Fai K AlAbdulghafoor, Carolyn D Summerbell, Helen V Worthington, Fujian Song, Lee Hooper. (2018) Omega‐3 fatty acids for the primary and secondary prevention of cardiovascular disease. Cochrane Systematic Review. https://doi.org/10.1002/14651858.CD003177.pub4 |
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| == Background ==
| | Abdelhamid AS, Brown TJ, Brainard JS, Biswas P, Thorpe GC, Moore HJ, Deane KHO, AlAbdulghafoor FK, Summerbell CD, Worthington HV, Song F, Hooper L. Omega‐3 fatty acids for the primary and secondary prevention of cardiovascular disease. Cochrane Database of Systematic Reviews 2018, Issue 11. Art. No.: CD003177. DOI: 10.1002/14651858.CD003177.pub4. |
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| ''The Background section should explain the background to the study, its aims, a summary of the existing literature and why this study was necessary or its contribution to the field.
| | 24. Zheng J, Huang T, Yu Y, Hu X et al. Fish consumption and CHD mortality: an updated meta-analysis of seventeen cohort studies. Public Health Nutrition (2012) 15:4:725-737. DOI: https://doi.org/10.1017/S1368980011002254 |
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| == Methods ==
| | 61. Ignatius S, Delaney A, Haapasaari P. Socio-cultural values as a dimension of fisheries governance: the cases of Baltic salmon and herring. Forthcoming. |
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| the aim, design and setting of the study
| | Ignatius, S. H. M., Haapasaari, P. E., & Delaney, A. (2017). Socio-cultural values as a dimension of fisheries management: the cases of Baltic salmon and herring. 52. Abstract from BONUS SYMPOSIUM: Science delivery for sustainable use of the Baltic Sea living resources, Tallinna, Estonia. |
| the characteristics of participants or description of materials
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| a clear description of all processes, interventions and comparisons.
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| the type of statistical analysis used, including a power calculation if appropriate
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| === Modelling ===
| | '''Additional changes due to an additional round of minor improvements |
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| The overall aim of the study was to estimate health risks and benefits of important compounds (dioxins, dioxin-like PCBs, methylmercury, omega-3 fatty acids, and vitamin D) found in Baltic herring and salmon at current consumption levels. The assessment model was implemented in an open and modular way at Opasnet web-workspace. In practice, this means that all the data and code used for different parts, or modules, of the model are located on different pages at Opasnet. These pages are called knowledge crystals, as their structure and workflow follow certain rules (Tuomisto et al 2018, forthcoming). In this section, we give the overview and links to the module pages, and all details can be found from there.<sup>a</sup>
| | * Ethical permission was not needed in any of the study countries, according to national guidelines for research and data protection: Finland, Sweden (Lag (2003:460) om etikprövning av forskning som avser människor [https://www.riksdagen.se/sv/dokument-lagar/dokument/svensk-forfattningssamling/lag-2003460-om-etikprovning-av-forskning-som_sfs-2003-460]), Denmark (National Videnskabsetisk Komité. Hvad skal jeg anmelde? http://www.nvk.dk/forsker/naar-du-anmelder/hvilke-projekter-skal-jeg-anmelde), and Estonia (Riigi Teataja. Isikuandmete kaitse seadus RT 2007, 24, 127. https://www.riigiteataja.ee/akt/130122010011). Accessed 28 Nov 2019. |
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| The benefit-risk assessment was based on a modular Monte Carlo simulation model, which had a hierarchical Bayesian module for estimating dioxin concentrations. The input distributions were derived either directly from data or from scientific publications. If no published information was available (as was the case with e.g. disability weights for non-typical endpoints such as tolerable weekly intakes or infertility, we used author judgement and wide uncertainty bounds (these judgements are defended later in the text). The model was run with 5000 iterations using R statistical software (version 3.5.1, https://cran.r-project.org).
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| === Consumption survey === | | === Code for estimating TEQ from chinese PCB7 === |
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| A questionnaire survey to study consumer’s fish-eating habits in four Baltic Sea countries (Finland, Sweden, Estonia, and Denmark) was done at the end of 2016. Around 500 respondents for internet panel were enrolled in each country by a professional survey company Taloustutkimus Ltd. The questionnaire included 32 questions about the consumption amount of Baltic herring and salmon, reasons to eat to not to eat those species, and policies that may affect the amount eaten. The questionnaire is described in detail in another article (Pihlajamäki et al, 2018, forthcoming).
| | See Du et al, 2012. |
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| Based on the results, a model was developed to predict distributions of individual long-term fish consumption (in grams per day) in subgroups defined by country, gender, and age (45 years was used as the cut point). In addition, people's reactions to several policies were predicted based on their answers on preferences (consumption of Baltic herring or salmon is recommended or restricted; or the availability and usability of these species is promoted). These decision scenarios were used to alter the business as usual scenario, and compare results. Also a few technical scenarios were developed: what if nobody ate fish more than 3 g per day; and what if fish is considered a primary versus a secondary source of nutrients. The latter scenario is important if dose-responses are non-linear (as is the case with omega-3 fatty acids), because the incremental health benefits of a primary source are larger than those of a secondary source.
| | <rcode> |
| | library(OpasnetUtils) |
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| Population data for each country for year 2016 was available from Eurostat database. Data was separated for gender and age (18 – 45 years and > 45 years) groups.
| | objects.latest("Op_en3104", code_name="preprocess") # [[EU-kalat]] eu eu2 |
| | objects.latest("Op_en4017", code_name="initiate") # [[Toxic equivalency factor]] TEF |
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| === Concentrations === | | eu <- Ovariable( |
| | "eu", |
| | dependencies = data.frame( |
| | Name=c("euRaw", "TEF", "indexguide"), |
| | Ident=c(NA,"Op_en4017/initiate", NA) |
| | ), |
| | formula = function(...) { |
| | euRaw$Length<-as.numeric(as.character(euRaw$Length_mean_mm)) |
| | euRaw$Year <- as.numeric(substr(euRaw$Catch_date, nchar(as.character(euRaw$Catch_date))-3,100)) |
| | euRaw@marginal[colnames(euRaw@output) %in% c("Length","Year")] <- TRUE |
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| Size-specific PCDD/F and PCB concentration distributions for each fish species and country were estimated based on EU Fish II study and a hierarchical Bayesian model. The concentrations in Baltic herring were found out to be highly sensitive to fish size, while size-dependency was much weaker in salmon. The model assumed ca. 7 per cent annual decrease in dioxin concentrations, based on long time trend measured in Finland. The samples were caught between 2009 and 2010.
| | eu <- euRaw[,c(1:4, 10, 20, 21, 18)] # See below + Length, Year, Result |
| | colnames(eu@output)[1:5] <- c("THLcode", "Matrix", "Compound", "Fish", "N") |
| | |
| | temp <- eu * TEF |
| | temp$Equivalency <- "TEF" |
| | eu$Equivalency <- "Raw" |
| | eu <- combine(eu, temp) |
| | |
| | eu$Compound <- factor( # Compound levels are ordered based on the data table on [[TEF]] |
| | eu$Compound, |
| | levels = unique(c(levels(TEF$Compound), levels(eu$Compound))) |
| | ) |
| | eu$Compound <- eu$Compound[,drop=TRUE] |
| | |
| | return(eu) |
| | } |
| | ) |
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| The fish samples came mostly from the Bothnian Sea, which is an important area for Finnish and Swedish catch. The concentrations distributions for the studied countries ware derived from the concentration model results by scaling them with the average concentration on a catch area of interest relative to the average from Bothnian Sea<ref>REFERENCE ABOUT AVERAGE CONCENTRATIONS NEEDED!</ref>.
| | eu <- EvalOutput(eu, verbose=TRUE) |
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| {{argument|relat1=relevant attack|selftruth1=true|id=arg8317|type=truth|content=Fix the claim to the [[Goherr assessment]] that small and large herring were treated as separate species!|sign=--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 05:46, 20 November 2018 (UTC)}}
| | pcb7 <- c("PCB28.31","PCB52","PCB101","PCB118","PCB138","PCB153","PCB180") |
| | | eu2 <- eu[eu$Fish=="Baltic herring" & (eu$Equivalency=="TEF" | eu$Compound %in% pcb7) , ] |
| Concentrations were calculated as dioxin toxic equivalency quantities (TEQ) by using WHO 2005 toxic equivalency factor (TEF) values.<ref>Van den Berg M, Birnbaum LS, Denison M, De Vito M, Farland W, Feeley M, et al. The 2005 World Health Organization Reevaluation of Human and Mammalian Toxic Equivalency Factors for Dioxins and Dioxin-Like Compounds. Toxicological Sciences 2006;93:223–241 doi:10.1093/toxsci/kfl055.</ref> Levels of fatty acids and methylmercury in Baltic herring were based on measured data obtained from the Finnish Food Safety Authority, and those in salmon are based on scientific literature.
| | eu2 <- oapply(eu2, c("THLcode","Equivalency"), sum) |
| | | result(eu2)[eu2$Equivalency=="Raw"] <- 1 / result(eu2)[eu2$Equivalency=="Raw"] |
| Dioxin concentration distribution was estimated for Finnish catch of Baltic herring and salmon from the EU Fish 2 study. These distributions were then scaled by the ratio of the average concentration in a particular catch area vs. the Finnish catch area on the Bothnian Sea and Bay. The Danish and Estonian catch areas were assumed to be Baltic west of Bornholm and Gulf of Finland, respectively. The Swedish catch areas for herring and salmon were assumed to be Baltic Main Basin and Bothnian Sea and Bay, respectively. These areas were based on landing statistics.
| | eu2 <- oapply(eu2,"THLcode",prod) |
| | | eu2 <- eu2[eu2$THLcode!="09K0763",] # For some reason, Raw drops out. |
| === Exposures ===
| | View(eu2@output) |
| | | hist(eu$euResult*12.5) # The chinese PSB7 concentration was 12.5 ug/kg. |
| '''Intake of salmon and herring
| | </rcode> |
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| A Bayesian module was created with the JAGS package of R software to calculate intake of salmon and herring in each country utilizing the questionnaire-based consumption data. The original data was used to calculate distribution parameters. Output of the module was the amount of fish eaten by a random individual, expressed as g/day. The module with its code is accessible online on the knowledge crystal page ''Goherr: Fish consumption study''.
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| The assessment of '''[[Goherr:_Fish_consumption_study |consumption of fish]]''' was based on a survey conducted by Taloustutkimus Ltd in the four study countries. Around 500 adults were recruited from each country, and consumption of fish, especially that of Baltic salmon and herring, was asked. Also, we asked reasons for eating or not eating fish and factors that would increase or reduce fish consumption. Gender and age (18-45 or 45+) were separated in the model.
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| '''[[EU-kalat|Concentrations of dioxins and PCBs in fish]]''' were based on EU Fish 2 study conducted by THL in 2009. The results were based on pooled and individual fish samples (98 Baltic herring and 9 salmon samples) and analysed for 17 dioxin and 37 PCB congeners. Toxic equivalent quantities (TEQ) were used by multiplying each congener concentration with its potential to induce dioxin-like effects ([[Toxic equivalency factor|toxic equivalency factor]], TEF) and summing up. Size-specific concentration distributions were estimated for salmon and herring, and dioxin and PCB TEQs using linear regression and hierarchical Bayesian modelling using R (version 3.4.3 and JAGS package, http://cran.r-project.org/). Herring sizes and dioxin concentrations in different scenarios came from the fish growth model by SLU applied in BONUS GOHERR project; those results are published elsewhere (##REF).
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| '''Other concentrations'''. [[Concentrations of beneficial nutrients in fish]] were based on published data and a dataset obtained from the Finnish Food Safety Authority Evira. [[Mercury concentrations in fish in Finland]] were based on Kerty database produced by the Finnish Environment Institute.
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| '''Exposures to pollutants and nutrients''' were simply products of consumption amounts and concentrations in the consumed fish. An exception to this were the infant's exposures to [[Infant's dioxin exposure|dioxin]] and [[ERF of methylmercury#Data|methylmercury]] during pregnancy and breast-feeding, as they were derived from the mother's exposure using simple toxicokinetic models.
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| === Exposure-responses ===
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| '''[[Exposure-response function]]s''' were derived for all relevant pollutants and nutrients. [[ERF_of_dioxin | Exposure-response functions of dioxins]] were derived for several endpoints. Tooth defects were based on an epidemiological study in Finland<ref name="alaluusua1996"/>. Cancer morbidity was based on U.S.EPA dioxin risk assessment<ref>U.S.EPA. Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisory. Volume 2: Risk Assessment and Fish Consumption Limits, 3rd Edition. 2000. Table 3-1.</ref>. Tolerable daily intake was based on EC Scientific Committee on Food recommendation<ref>EC Scientific Committee on Food. (2001) Opinion of the Scientific Committee on Food on the risk assessment of dioxins and dioxin-like PCBs in food. CS/CNTM/DIOXIN/20 final [https://ec.europa.eu/food/sites/food/files/safety/docs/cs_contaminants_catalogue_dioxins_out90_en.pdf]</ref>. [[ERF of omega-3 fatty acids|Exposure-response functions for omega-3 fatty acids]] on coronary heart disease and stroke mortalities were from a previous risk assessment<ref>Cohen, J.T., PhD, Bellinger, D.C, PhD, W.E., MD, Bennett A., and Shaywitz B.A. 2005b. A Quantitative Analysis of Prenatal Intake of n-3 Polyunsaturated Fatty Acids and Cognitive Development. American Journal of Preventive Medicine 2005;29(4):366–374).</ref>. [[ERF_of_methylmercury |Exposure-response function of methylmercury]] on child's intelligence quotient was based on a previous risk assessment<ref>Cohen JT, Bellinger DC, Shaywitz BA. A quantitative analysis of prenatal methyl mercury exposure and cognitive development. Am J Prev Med. 2005 Nov;29(4):353-65.</ref>. [[ERFs of vitamins|Exposure-response function for vitamin D]] was a step function based on the daily intake recommendations for adults in Finland<ref>Finnish Nutrition Recommendations 2014 [https://www.evira.fi/globalassets/vrn/pdf/ravitsemussuositukset_2014_fi_web.3_es-1.pdf]</ref>.
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| {| {{prettytable}}
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| |+'''Table ##. Exposure-response functions used in the assessment.
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| |----
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| ! Exposure agent|| Response|| Esposure-response unit|| Exposure-response function|| References
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| |----
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| || TEQ (Intake through placenta and mother's milk)|| Male infertility due to sperm concentration decrease|| pg /g in boy's body fat||0.00006+-0.00004||<ref name="minguez2017"/> Mother's exposure must be converted to child's exposure (measured as pg /g fat) using ovariable Infant's dioxin exposure.
| |
| |----
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| || TEQ (Intake through placenta and mother's milk)|| Developmental dental defects|| log (pg /g) in child's body fat|| 0.26 +- 0.12||
| |
| |----
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| || TEQ|| Cancer morbidity|| pg/kg/day|| 0.000032; 0.000035; 0.000156 ||
| |
| |----
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| || TEQ|| Current EFSA dioxin recommendation: tolerable daily intake|| pg/kg/week|| 14 ||
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| |----
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| || TEQ|| Suggested EFSA dioxin recommendation: tolerable daily intake|| pg/kg/week|| 2 ||
| |
| |----
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| || DHA|| Loss in child's IQ points|| mg/day|| -0.0013 (-0.0018 - -0.0008)||
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| |----
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| || Omega3|| CHD2 mortality|| mg/day|| -0.17 (-0.25 - -0.088)||
| |
| |----
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| || Omega3|| Stroke mortality|| mg/day|| -0.12 (-0.25 - 0.01)||
| |
| |----
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| || Vitamin D|| Vitamin D recommendation|| µg/day|| 100||
| |
| |----
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| || MeHg|| Loss in child's IQ points|| mg/kg/day|| 6.533 (0 - 14)||
| |
| |----
| |
| |}
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| ==== Sperm concentration ====
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| In humans, sperm concentrations have been shown to decrease permanently if boys are exposed to dioxins before nine years of age. The results come from Seveso<ref>Mocarelli P et al. Dioxin exposure, from infancy to puberty, produces endocrine disruption and affects human semen quality. Environmental Health Perspectives 2008;116:1</ref><ref>Mocarelli P. et al. Perinatal exposure to low doses of dioxin can permanently impair human semen quality. Environmental Health Perspectives 2011;119:5.</ref> and a Russian children's study<ref name="minguez2017">Minguez-Alarcon L. et al. A longitudinal study of peripubertal serum organochlorine concentrations and semen parameters in young men: the Russian children's study. Environmental Health Perspectives 2017;125:3.</ref>.
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| EFSA recently assessed this risk from the Russian children's study and concluded that significant effect was seen already in the second quartile with median PCDD/F TEQ concentration 10.9 pg/g fat, when measured from the serum of the boys at the age of ca. 9 years. Sperm concentration mean was ca. 65 (95 % CI 50-80) million/ml in the lowest quartile, while in all other quartiles the concentration was ca. 40 (96 % CI 30-55) million/ml. Due to the shape of the effect, we used a non-linear exposure-response curve with half of the maximum effect occurring at TEQ concentration 10.5 pg/g fat.
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| However, sperm concentration as such is not a health effect. It only manifests itself if the concentration is low enough to prevent conception in a reasonable time window, say five years. According to a review, the success rate of couples who try to get pregnant is 65 % in 6 months if the sperm concentration is above 40 million/ml.<ref>Sharpe1 RM. Sperm counts and fertility in men: a rocky road ahead. EMBO Rep. 2012;13:398–403. doi:10.1038/embor.2012.50.</ref> Below that concentration, the probability is fairly proportional to the sperm concentration.
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| Based on this, we estimated that (assuming independent probabilities between 6-month periods), the probability of not getting pregnant in five years follows this curve:
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| P(infertility after 5 a) = (1 - 0.65 (1+ \frac{-0.39c}{c + 10.5 pg/g})^{10}
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| where c is the dioxin concentration in boy's fat tissue. For details, see the knowledge crystal ''ERF of dioxin'' at Opasnet.
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| This curve is pretty linear below TEQ concentration 50 pg/g with slope ca. 0.00006 g/pg, meaning that for each 1 pg/g increase in dioxin concentration the boy's fat tissue (or serum fat), there is an incrementally increased probability of 0.00006 that he cannot get a child even after five years of trying.
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| ==== Tooth defects ====
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| Alaluusua and coworkers have published several studies on dioxin exposure in small children and the development of permanent molar teeth. They have found defects in both general population in Finland from the exposures in the 1980's <ref name="alaluusua1996">Alaluusua S, Lukinmaa PL, Vartiainen T, Partanen M, Torppa J, Tuomisto J. Polychlorinated dibenzo-p-dioxins and dibenzofurans via mother's milk may cause developmental defects in the child's teeth. Environ Toxicol Pharmacol. 1996;1:193-7.</ref>
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| <ref name="alaluusua1999">Alaluusua S, Lukinmaa PL, Torppa J, Tuomisto J, Vartiainen T. Developing teeth as biomarker of dioxin exposure. Lancet. 1999;353:206.</ref>
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| and children exposed during the Seveso accident<ref name="Alaluusua">Alaluusua S, Calderara P, Gerthoux PM, Lukinmaa P-L, Kovero O, Needham L, et al. Developmental dental aberrations after the dioxin accident in Seveso. Environ Health Perspect. 2004;112:1313-8.</ref>
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| Based on these studies, we approximated that the effect is linearly correlated with the logarithm of the dioxin concentration in the child.
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| === Background disease levels===
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| Background disease levels were needed for stroke and cardiovascular diseases and were obtained from The Institute for Health Metrics and Evaluation (IHME).
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| '''[[Burden of disease]]''' was estimated in two alternative ways: if the burden of a particular disease in the target population was known, the [[attributable risk|attributable fraction]] of a particular compound exposure was calculated. If it was not known, the excess number of cases due to the exposure was estimated using [[health impact assessment]], and this was multiplied by the years under disease per case and the disability weight of the disease. If the exposure-response function was relative to background risk of the disease, [[disease risk]]s from Finland were used for all countries. Population data was from Eurostat (http://ec.europa.eu/eurostat). Disability weights and durations of diseases were based on the estimates from the Institute for Health Metrics and Evaluation (https://healtdata.org), adjusted using author judgement when appropriate estimates were not available.
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| === Disability weights ===
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| Childlessness is said to be "tragedy of life", so the disability weight could be in the order of 0.1 DALY per year permanently (50 years). However, the disability weight applies to only half of the children (boys), and we can fairly assume that half of the couples get a satisfactory solution via adoption, in-vitro fertilisation or other treatments. Therefore, the impact is 0.1*50*0.5*0.5 DALY/case = 1.25 DALY/case, with rather high uncertainty (say, 0-2.5 DALY/case)
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| == Results == | |
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| ''This should include the findings of the study including, if appropriate, results of statistical analysis which must be included either in the text or as tables and figures.
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| We can also consider men that have already decreased sperm concentrations from an unrelated reason. Dioxin is likely to reduce that even further. For example, if the sperm concentration is 10 million/ml, the probability of infertility in five years is 0.32, and that increases to 0.48 at dioxin concentration 100 pg/g. This exposure-response is non-linear, with half of the effect occurring already at 10 pg/g. If ten percent of the population had this low semen concentration and if 20 % of boys exceed 10 pg/g (as seems to be the case with [[Goherr assessment]]), then we would see for example in Finland 25000 boys/year * 0.1 with low fertility * 0.2 with high dioxin * 0.08 absolute increase in infertility = 40 cases per year and thus 50 DALY.
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| [[File:Goherr benefit-risk assessment fig3.svg|thumb|500px|Dioxin concentrations have reduced a lot since 1990. The same trend have existed since the 1970's (data not shown).]]
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| [[File:Goherr benefit-risk assessment fig5.svg|thumb|500px|Dioxin concentration distributions in Baltic fish after size-related policies. With active policy to not use large (>17 cm) Baltic herring ("Ban large"), the concentrations on the plate would be clearly lower than nowadays, while the promotion of smaller herring size has a smaller effect ("New products") compared with the business as usual scenario ("BAU").]]
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| [[File:Goherr benefit-risk assessment fig10.svg|thumb|500px|Individual change in consumption after a recommendation to either increase or reduce the fish intake. The outcome depends on previous consumption but not much on population subgroup. Also, although some people obey the recommendation to reduce consumption, almost an equal amount does the opposite, and most do not change. This phenomenon is seen already at current intakes below 5 g/day, where most of the population is.]]
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| [[File:Goherr benefit-risk assessment fig12.svg|thumb|500px|Fish consumption distributions of Baltic herring and salmon in different subgroups of the studied countries. There is large individual variation (almost hundredfold) in fish consumption in most subgroups. There is also a large fraction of people who do not eat these fishes at all (25-90 % with Baltic herring, 70-90 % with Baltic salmon).]]
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| [[File:Goherr benefit-risk assessment fig15.svg|thumb|500px|Cumulative dioxin exposure distributions shown by subgroup and country. Few young females exceed the current tolerable daily intake any more, as both concentrations and consumption have decreased. The new tolerable weekly intake is exceeded by a much larger fraction. {{argument|relat1=relevant attack|selftruth1=true|id=arg6931|type=truth|content=Change these from TDI to TWI. And add new TWI line.|sign=--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 06:29, 19 November 2018 (UTC)}}]] | |
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| [[File:Goherr benefit-risk assessment fig22.svg|thumb|500px|Burden of disease of eating Baltic fish (expected value on the individual level). When looking that the net health benefits, it is clear that old age groups benefit a lot from eating fish despite risks. The impacts overall are much smaller in young age groups, and in women the critical issue is effects of child's intelligence quotient (IQ) and tooth defects, not the health impacts to the woman herself.{{argument|relat1=relevant attack|selftruth1=true|id=arg6931|type=truth|content=Remove policy "inconsistent".|sign=--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 06:29, 19 November 2018 (UTC)}}]]
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| [[File:Goherr benefit-risk assessment fig28.svg|thumb|500px|Burden of disease of the most important environmental health factors in Finland. In a bigger picture, Baltic fish and its health hazards are only one of the many environmental health risks. It is not even close to the largest ones, but it may be in the top 10 list.]]
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| '''Value of information analyses
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| For detailed results, see [http://en.opasnet.org/en-opwiki/index.php?title=Special:RTools&id=vRYbR54ddT2UsBjg model run on 18.11.2018]. Value of information was looked at in three parts, where a bunch of similar decisions were considered together. In these VOI analyses, infertility was used as the outcome for the sperm concentration effect, while tolerable weeksly intakes (both the current "Dioxin TWI" and the new suggested "TWI 2018") were ignored.
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| Value of information was calculated for the total burden of disease in a random population subgroup in the four study countries, but using uncertainties for individual people. This approach ensures that value of information is not underestimated, because at population level many uncertainties are smaller than at individual level.
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| * Select herring size
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| ** There is practically no expected value of perfect information (EVPI) (only 1.5 DALY/a) because ''Ban large'', i.e. switching to small herring is in most cases better than other alternatives. However, also other options are beneficial, and the expected value of including that option is 16 DALY/a.
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| ** If that option is excluded, EVPI increases to 8 DALY/a.
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| * Consider background and limit maximal fish intake to 3 g/d are evaluated at the same time.
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| ** EVPI is slightly higher than with herring size, 51 DALY. This is because there is no obvious single decision option to choose.
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| ** Dropping the option Background=No would cost 1880 DALY/a, demonstrating that that is clearly a good choice. However, whether background should be considered or not is not an actionable decision but rather a value judgement about how the situation should be seen. In practice, if you consider background intake (Background=Yes), you ignore a large amount of health benefits from omega3 fatty acids in fish. Some people may say that ignoring it is exactly what you should do because those omega3 fatty acids can easily be received from sources that do not have pollutants (the default in this assessment), while others say that fish and other natural foods are the primary source, and omega3 pills and other food supplements should only be used if undernourished.
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| ** If you always consider background intake, then the model uncertainties decrease, and your EVPI is lower (10 DALY/a). The largest EVPI (42 DALY/a) is obtained when fish intake is not limited to 3 g/d; this is because there is more room for benefits leveling off and relative importance of risks increasing, thus increasing uncertainty to decision making.
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| * Improved information (including availability and usability of fish) and consumption recommendations.
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| ** EVPI with these decisions is 40 DALY/a, so there is some uncertainty about what to do.
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| ** The most important decision option is to increase information and fish availability (145 DALY/a), while any of the other options can be excluded without much change in expected value.
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| In a previous analysis we used tolerable weeksly intake instead of infertility ([http://en.opasnet.org/en-opwiki/index.php?title=Special:RTools&id=cPBeTD3VkgPcW0yV model run on 20.4.2018, data not shown]). The disability weight used for tolerable weekly dioxin intake is highly uncertain in the model (hundredfold uncertainty 0.0001 - 0.01 DALY/case of exceedance). Therefore, presumably it would be very important to know the actual value that the society wants to allocate to this impact. But actually it is not, as knowing the value has expected value of partial perfect information (EVPPI) of only 12 DALY/a. The reason for this seems to be that this disability weight rarely becomes so high that a decision maker would actually regret fish-promoting policies.
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| == Discussion ==
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| ''This section should discuss the implications of the findings in context of existing research and highlight limitations of the study.
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| == Conclusions ==
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| ''This should state clearly the main conclusions and provide an explanation of the importance and relevance of the study reported.
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| == List of abbreviations ==
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| : DHA: docosahexaenic acid
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| : EFSA: European Food Safety Authority
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| : EPA: eicosapentaenic acid
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| : TEF: toxic equivalency factor
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| : TEQ: toxic equivalency quantity
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| : WHO: World Health Organisation
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| == Declarations ==
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| === Ethics approval and consent to participate ===
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| An online survey was performed to adult consumers in Denmark, Estonia, Finland, and Sweden by Taloustutkimus Ltd. We asked about fish eating habits but not about health or other sensitive issues. We did not ask or collect identity information of the respondents, except age, gender, and country, which were used for classification in analyses. The survey did not involve any interventions. Due to these reasons, there was no need for ethical approval according to the THL guidance.
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| === Consent for publication ===
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| Not applicable.
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| ''If your manuscript contains any individual person’s data in any form (including any individual details, images or videos), consent for publication must be obtained from that person, or in the case of children, their parent or legal guardian. All presentations of case reports must have consent for publication.
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| ''You can use your institutional consent form or our consent form if you prefer. You should not send the form to us on submission, but we may request to see a copy at any stage (including after publication).
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| ''See our editorial policies for more information on consent for publication.
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| ''If your manuscript does not contain data from any individual person, please state “Not applicable” in this section.
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| === Availability of data and materials ===
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| The whole benefit-risk assessment was performed online at http://en.opasnet.org/w/Goherr_assessment, and all details (including data, code, results, descriptions, and discussions) are openly available, except for the personal data from the consumer survey. The consumer survey data was converted to and published as synthetic data, i.e. data that does not represent any real individuals but that has similar statistical properties as the actual data.
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| The datasets generated and analysed during the current study, together with the other material mentioned above, are available in the IDA research data repository, [###PERSISTENT WEB LINK TO DATASETS]
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| === Competing interests ===
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| The authors declare that they have no competing interests. | |
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| === Funding ===
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| This work resulted from the BONUS GOHERR project (Integrated governance of Baltic herring and salmon stocks involving stakeholders, 2015-2018) that was supported by BONUS (Art 185), funded jointly by the EU, the Academy of Finland and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning.
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| === Authors' contributions ===
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| JT planned the assessment design, performed most of the analyses, and wrote the first draft of the manuscript based on input from other authors. PH coordinated the project and participated in designing and linking of this work to other parts of the project. AA designed and performed the questionnaire study. PM participated in the discussions about the design and interpretation of results. All authors read and approved the final manuscript.
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| === Acknowledgements ===
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| We thank all BONUS GOHERR researchers and stakeholder meeting participants, who participated in lively discussions about the importance of Baltic fisheries management and health.
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| === Authors' information ===
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| No specific information.
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| == Endnotes ==
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| ''Endnotes should be designated within the text using a superscript lowercase letter and all notes (along with their corresponding letter) should be included in the Endnotes section. Please format this section in a paragraph rather than a list.
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| <sup>a</sup> We refer to knowledge crystals using ''italics''. This indicates that there is a page with detailed data and codes at Opasnet (e.g. ''ERF of dioxin''), and that knowledge crystal can be accessed by the respective link (e.g. http://en.opasnet.org/w/ERF_of_dioxin).
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| == References ==
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| <references/> | |
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| Examples of the Vancouver reference style are shown below.
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| See our editorial policies for author guidance on good citation practice
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| Web links and URLs: All web links and URLs, including links to the authors' own websites, should be given a reference number and included in the reference list rather than within the text of the manuscript. They should be provided in full, including both the title of the site and the URL, as well as the date the site was accessed, in the following format: The Mouse Tumor Biology Database. http://tumor.informatics.jax.org/mtbwi/index.do. Accessed 20 May 2013. If an author or group of authors can clearly be associated with a web link, such as for weblogs, then they should be included in the reference.
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| Example reference style:
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| Article within a journal
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| Smith JJ. The world of science. Am J Sci. 1999;36:234-5.
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| Article within a journal (no page numbers)
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| Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Medicine. 2013;11:63.
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| Article within a journal by DOI
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| Slifka MK, Whitton JL. Clinical implications of dysregulated cytokine production. Dig J Mol Med. 2000; doi:10.1007/s801090000086.
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| Article within a journal supplement
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| Frumin AM, Nussbaum J, Esposito M. Functional asplenia: demonstration of splenic activity by bone marrow scan. Blood 1979;59 Suppl 1:26-32.
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| Book chapter, or an article within a book
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| Wyllie AH, Kerr JFR, Currie AR. Cell death: the significance of apoptosis. In: Bourne GH, Danielli JF, Jeon KW, editors. International review of cytology. London: Academic; 1980. p. 251-306.
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| OnlineFirst chapter in a series (without a volume designation but with a DOI)
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| Saito Y, Hyuga H. Rate equation approaches to amplification of enantiomeric excess and chiral symmetry breaking. Top Curr Chem. 2007. doi:10.1007/128_2006_108.
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| Complete book, authored
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| Blenkinsopp A, Paxton P. Symptoms in the pharmacy: a guide to the management of common illness. 3rd ed. Oxford: Blackwell Science; 1998.
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| Online document
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| Doe J. Title of subordinate document. In: The dictionary of substances and their effects. Royal Society of Chemistry. 1999. http://www.rsc.org/dose/title of subordinate document. Accessed 15 Jan 1999.
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| Online database
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| Healthwise Knowledgebase. US Pharmacopeia, Rockville. 1998. http://www.healthwise.org. Accessed 21 Sept 1998.
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| Supplementary material/private homepage
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| Doe J. Title of supplementary material. 2000. http://www.privatehomepage.com. Accessed 22 Feb 2000.
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| University site
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| Doe, J: Title of preprint. http://www.uni-heidelberg.de/mydata.html (1999). Accessed 25 Dec 1999.
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| FTP site
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| Doe, J: Trivial HTTP, RFC2169. ftp://ftp.isi.edu/in-notes/rfc2169.txt (1999). Accessed 12 Nov 1999.
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| Organization site
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| ISSN International Centre: The ISSN register. http://www.issn.org (2006). Accessed 20 Feb 2007.
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| Dataset with persistent identifier
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| Zheng L-Y, Guo X-S, He B, Sun L-J, Peng Y, Dong S-S, et al. Genome data from sweet and grain sorghum (Sorghum bicolor). GigaScience Database. 2011. http://dx.doi.org/10.5524/100012.
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| == Figures, tables and additional files ==
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