Health effects of Baltic herring and salmon: a benefit-risk assessment

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Citation of this page: Jouni T. Tuomisto, Arja Asikainen, Päivi Meriläinen, Päivi Haapasaari: Health effects of Baltic herring and salmon: a benefit-risk assessment. Opasnet 2019. [1]. Accessed 21 Nov 2024.
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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 [2]. Thank you for your interest.

• Swedish Food Safety Authority about EFSA dioxin assessment

Changes to the revision 2019-09-24:

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.

→ 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.

Due to these reasons and according to the national guidelines, there was no need for ethical approval[65].

→ 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.)

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

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

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

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.

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

61. Ignatius S, Delaney A, Haapasaari P. Socio-cultural values as a dimension of fisheries governance: the cases of Baltic salmon and herring. Forthcoming.

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.

Additional changes due to an additional round of minor improvements

• 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 [3]), 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.

Code for estimating TEQ from chinese PCB7

See Du et al, 2012.

+ Show code- Hide code library(OpasnetUtils) objects.latest("Op_en3104", code_name="preprocess") # [[EU-kalat]] eu eu2 objects.latest("Op_en4017", code_name="initiate") # [[Toxic equivalency factor]] TEF 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$Catch_date))-3,100)) euRaw@marginal[colnames(euRaw@output) %in% c("Length","Year")] <- TRUE eu <- euRaw[,c(1:4, 10, 20, 21, 18)] # See below + Length, Year, Result colnames(eu@output)[1:5] <- c("THLcode", "Matrix", "Compound", "Fish", "N") temp <- eu * TEF temp$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$Compound[,drop=TRUE] return(eu) } ) eu <- EvalOutput(eu, verbose=TRUE) pcb7 <- c("PCB28.31","PCB52","PCB101","PCB118","PCB138","PCB153","PCB180") eu2 <- eu[eu$Fish=="Baltic herring" & (eu$Equivalency=="TEF" | eu$Compound %in% pcb7) , ] eu2 <- oapply(eu2, c("THLcode","Equivalency"), sum) result(eu2)[eu2$Equivalency=="Raw"] <- 1 / result(eu2)[eu2$Equivalency=="Raw"] eu2 <- oapply(eu2,"THLcode",prod) eu2 <- eu2[eu2$THLcode!="09K0763",] # For some reason, Raw drops out. View(eu2@output) hist(eu$euResult*12.5) # The chinese PSB7 concentration was 12.5 ug/kg.