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

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|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.


== 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]


* Title: Health effects of Baltic herring and salmon: a benefit-risk assessment
Changes to the revision 2019-09-24:
* Authors:
*: Jouni T. Tuomisto, jouni.tuomisto[]thl.fi, (corresponding author), National Institute for Health and Welfare, Kuopio, Finland.
*: Arja Asikainen, arja.asikainen[]thl.fi, National Institute for Health and Welfare, Kuopio, Finland.
*: Päivi Meriläinen, paivi.merilainen@thl.fi, National Institute for Health and Welfare, Kuopio, Finland.
*: Päivi Haapasaari, paivi.haapasaari[]helsinki.fi, University of Helsinki, Finland.


== 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.


'''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.


'''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 Agency. 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].


'''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.)


'''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 exeeding 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


== 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


Fish consumption, dioxins, methylmercury, benefit-risk assessment, health impact, sperm concentration, Baltic Sea, knowledge crystal, food recommendation, European Food Safety Agency 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


== 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.


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


== 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.


    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
    a clear description of all processes, interventions and comparisons.
    the type of statistical analysis used, including a power calculation if appropriate


A questionnaire 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).
'''Additional changes due to an additional round of minor improvements


Based on the results, a model was developed to predict distributions of individual long-term consumption (in grams per day) in subgroups defined by country, gender, and age (45 years was used as the cutpoint). In addition, people's reactions to several policies were prediceted based on their answers (consumption of Baltic herring or salmon is recommended or restricted; or the availability and usability of these species is promoted). There 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 of 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.
* 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.


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.


PCDD/F and PCB concentration distributions for each fish species and country were estimated in the following way:
=== Code for estimating TEQ from chinese PCB7 ===
EU-kalat study is used as the reference, because it has a large number of measurements. They come mostly from Bothnian Sea (subdivision 30).
The distributions are like those from the EU-kalat study, except that the means are scaled based on the area of interest relative to the reference (see table below).
The relative standard deviations are assumed to be the same for each fish population.
Baltic herring (>= 17 cm) and Small Baltic herring (<17 cm) are treated in the model as if they were separate species. Estonians are assumed to eat only small, others only large Baltic herring


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 Evira and from literature for Baltic salmon.
See Du et al, 2012.


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.
<rcode>
library(OpasnetUtils)


=== Exposure-responses ===
objects.latest("Op_en3104", code_name="preprocess") # [[EU-kalat]] eu eu2
objects.latest("Op_en4017", code_name="initiate") # [[Toxic equivalency factor]] TEF


{| {{prettytable}}
eu <- Ovariable(
|+'''Table ##. Exposure-response functions used in the assessment.
  "eu",
|----
  dependencies = data.frame(
! Exposure agent|| Response|| ER unit|| ERF
    Name=c("euRaw", "TEF", "indexguide"),
|----
    Ident=c(NA,"Op_en4017/initiate", NA)
|| TEQ|| Yes or no developmental dental defects incl. agenesis|| log (pg /g)|| 0.26 +- 0.12
  ),
|----
  formula = function(...) {
|| TEQ|| Cancer morbidity|| pg/kg/day|| 0.000032; 0.000035; 0.000156
    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))
|| TEQ|| Dioxin recommendation tolerable daily intake|| pg/kg/day|| 1
    euRaw@marginal[colnames(euRaw@output) %in% c("Length","Year")] <- TRUE
|----
|| DHA|| Loss in child's IQ points|| mg/day|| -0.0013 (-0.0018 - -0.0008)
|----
|| Omega3|| CHD2 mortality|| mg/day|| -0.17 (-0.25 - -0.088)
|----
|| Omega3|| Stroke mortality|| mg/day|| -0.12 (-0.25 - 0.01)
|----
|| Vitamin D|| Vitamin D recommendation|| µg/day|| 100
|----
|| MeHg|| Loss in child's IQ points|| mg/kg/day|| 6.533 (0 - 14)
|----
|}


Background disease levels
    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)
  }
)


Background disease levels were needed for stroke and cardiovascular diseases and were obtained from The Institute for Health Metrics and Evaluation (IHME).
eu <- EvalOutput(eu, verbose=TRUE)


Models
pcb7 <- c("PCB28.31","PCB52","PCB101","PCB118","PCB138","PCB153","PCB180")
 
eu2 <- eu[eu$Fish=="Baltic herring" & (eu$Equivalency=="TEF" | eu$Compound %in% pcb7) , ]
Intake of salmon and herring
eu2 <- oapply(eu2, c("THLcode","Equivalency"), sum)
 
result(eu2)[eu2$Equivalency=="Raw"] <- 1 / result(eu2)[eu2$Equivalency=="Raw"]
A Bayesian model was created with the R - program 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, which were then used to model population representative sample of 1 000 individuals. Output of the model was amount of fish eaten as g/day. The model with its code is accessible on-line
eu2 <- oapply(eu2,"THLcode",prod)
 
eu2 <- eu2[eu2$THLcode!="09K0763",] # For some reason, Raw drops out.
The assessment model is implemented in a modular way in Opasnet. In practice, this means that the data and code used for different parts of the model is located at different pages in Opasnet. In this section, we give the overview and links to the module pages, and all details can be found from there. The whole idea of Opasnet is that different modules can be used in different assessments simultaneously, and that updates in any module are fully reflected in all assessments when they are rerun.
View(eu2@output)
 
hist(eu$euResult*12.5) # The chinese PSB7 concentration was 12.5 ug/kg.
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.
</rcode>
 
'''[[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).
 
'''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.
 
'''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.
 
'''[[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>.
 
'''[[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.
 
== Results ==
 
''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.
 
== Discussion ==
 
''This section should discuss the implications of the findings in context of existing research and highlight limitations of the study.
 
== Conclusions ==
 
''This should state clearly the main conclusions and provide an explanation of the importance and relevance of the study reported.
 
== List of abbreviations ==
 
: EFSA: European Food Safety Agency
: TEF: toxic equivalency factor
: TEQ: toxic equivalency quantity
: WHO: World Health Organisation
 
== Declarations ==
 
=== Ethics approval and consent to participate ===
 
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.
 
=== Consent for publication ===
 
Not applicable.
 
''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.
 
''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).
 
''See our editorial policies for more information on consent for publication.
 
''If your manuscript does not contain data from any individual person, please state “Not applicable” in this section.
 
=== Availability of data and materials ===
 
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.
 
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]
 
=== Competing interests ===
 
The authors declare that they have no competing interests.
 
=== Funding ===
 
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.
 
=== Authors' contributions ===
 
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.
 
=== Acknowledgements ===
 
We thank all BONUS GOHERR researchers and stakeholder meeting participants, who participated in lively discussions about the importance of Baltic fisheries management and health.
 
=== Authors' information ===
 
No specific information.
 
== Endnotes ==
 
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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Latest revision as of 13:58, 28 November 2019


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.

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


Code for estimating TEQ from chinese PCB7

See Du et al, 2012.

+ Show code

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