Benefit-risk assessment of Baltic herring and salmon intake

From Opasnet
Jump to: navigation, search
Progression class
In Opasnet many pages being worked on and are in different classes of progression. Thus the information on those pages should be regarded with consideration. The progression class of this page has been assessed:
This page is a full draft
This page has been written through once, so all important content is already where it should be. However, the content has not been thoroughly checked yet, and for example important references might still be missing.
The content and quality of this page is being curated by THL. THL LOGO EN WEB 272x66px.jpg

The quality was last checked: 2018-04-21.

Schematic picture of the health benefit-risk model for Baltic herring and salmon intake.

Assessment presentation · show ready-made model results


This assessment is part of the WP5 work in Goherr project. Purpose is to evaluate health benefits and risks caused of eating Baltic herring and salmon in four Baltic sea countries (Denmark, Estonia, Finland and Sweden). This assessment is currently on-going.


What are the current population level health benefits and risks of eating Baltic herring and salmon in Finland, Estonia, Denmark and Sweden? How would the health effects change in the future, if consumption of Baltic herring and salmon changes due to actions caused by different management scenarios of Baltic sea fish stocks?

Intended use and users

Results of this assessment are used to inform policy makers about the health impacts of fish. Further, this assessment will be combined with the results of the other Goherr WPs to produce estimates of future health impacts of Baltic fish related to different policy options. Especially, results of this assessment will be used as input in the decision support model built in Goherr WP6.


  • University of Helsinki: Sakari Kuikka, Päivi Haapasaari, Suvi Ignatius, Kirsi Hoviniemi
  • National Institute for Health and Welfare (THL): Jouni Tuomisto, Arja Asikainen
  • University of Oulu: Timo P. Karjalainen, Simo Sarkki, Mia Pihlajamäki
  • Swedish University of Agricultural Sciences (SLU): Anna Gårdmark, Johan Östergren, Magnus Huss, Andreas Bryhn
  • University of Aalborg/Innovative Fisheries Management (IFM-AAU): Alyne Delaney, Jesper Raakjaer
  • Stakeholders needed in the assessment: fisher's associations, agricultural/fisheries ministries in Finland, Sweden, Estonia, Denmark.


  • Four baltic sea countries (Denmark, Estonia, Finland, Sweden)
  • Current situation (fish use year 2016, pollutant levels in fish year 2010)
  • Estimation for future (not year specific)
  • Area considered: Sweden, Finland, Denmark, Estonia. For detailed herring/salmon stock modelling, only the Bothnian Sea and Gulf of Bothnia is considered.
  • Policies considered: We will build and explore four integrative scenarios for the future of Baltic salmon and herring. See below.
  • This assessment looks at health only. Goherr as a project will consider wider objectives: threats to and state of the fish stocks; impacts and governance responses. See below.

Decisions and scenarios

ObsNumDecision makerDecisionOptionVariableCellChangeResultDescription
10HELCOMInfo.improvementsBAUeffinfoReplace0Current availability of and chemicals in herring and salmon
21HELCOMInfo.improvementsYeseffinfoIdentityBetter availability of and less chemicals in herring and salmon
30National foodNational food safety authority authorityRecomm.herringBAUeffrecommFish:HerringReplace0Authorities recommendations about Baltic herring do not change
42National food safety authorityRecomm.herringEat moreeffrecommFish:Herring;Recommendation:Eat lessReplace0Authorities recommend to eat more Baltic herring
52National food safety authorityRecomm.herringEat lesseffrecommFish:Herring;Recommendation:Eat moreReplace0Authorities recommend to eat less Baltic herring
60National food safety authorityRecomm.salmonBAUeffrecommFish:SalmonReplace0Authorities recommendations about Baltic salmon do not change
73National food safety authorityRecomm.salmonEat moreeffrecommFish:Salmon;Recommendation:Eat lessReplace0Authorities recommend to eat more Baltic salmon
83National food safety authorityRecomm.salmonEat lesseffrecommFish:Salmon;Recommendation:Eat moreReplace0Authorities recommend to eat less Baltic salmon
90HELCOMSelect.sizeBAUsizesFish:Baltic herring;Lower:70Replace0Select herring size for consumption: only small, only large, or both
100HELCOMSelect.sizeBAUsizesFish:Baltic herring;Lower:120Replace0
114HELCOMSelect.sizeBan largesizesFish:Baltic herring;Lower:170Replace0
124HELCOMSelect.sizeBan largesizesFish:Baltic herring;Lower:220Replace0
134HELCOMSelect.sizeBan largesizesFish:Baltic herring;Lower:270Replace0
144HELCOMSelect.sizeNew productssizesFish:Baltic herringIdentity
150National food safety authorityBackgroundYesbgexposureIdentityConsider background from other sources
165National food safety authorityBackgroundNobgexposureReplace0Do not consider background from other sources
170National food safety authorityLimitNo limitamountIdentity
186National food safety authorityLimitMax 3 g/damountIdentity This should limit consumption to max 10 g per day but requires a function rather than dectable
190Risk assessorTime2018timeReplace2018Short timeline (2018 only)
207Risk assessorTime2010timeReplace2010Long timeline (1990, 2000, 2010, 2018)
217Risk assessorTime2000timeReplace2000
227Risk assessorTime1990timeReplace1990
230Risk assessorMixturesBAUconcIdentityAll compounds as micture in the model
248Risk assessorMixturesMeHgconcExposure_agent:MeHgReplace0Consider situation without MeHg
258Risk assessorMixturesDioxinconcExposure_agent:PCDDFReplace0Consider situation without PCDDF and PCB
268Risk assessorMixturesDioxinconcExposure_agent:PCBReplace0Consider situation without PCDDF and PCB
278Risk assessorMixturesDioxinconcExposure_agent:TEQReplace0Consider situation without PCDDF and PCB
288Risk assessorMixturesOmega3concExposure_agent:DHAReplace0Consider situation without DHA and EPA
298Risk assessorMixturesOmega3concExposure_agent:EPAReplace0Consider situation without DHA and EPA
308Risk assessorMixturesOmega3concExposure_agent:Omega3Replace0Consider situation without DHA and EPA
318Risk assessorMixturesVitamin DconcExposure_agent:Vitamin DReplace0Consider situation without MeHg
329Risk assessorTime2009timeReplace2009Same time as EU Fish2 study
339Risk assessorSelect.sizeAll sizessizesFish:Baltic herringIdentitySize fractions to include EU Fissh2 study
1effrecommRecommendationsumRemove the Eat more/less recommendation because it is replaced with more/less/BAU index.
2concconcSourcesumRemove redundant columns
3expoRawinfoSource,bgexposureSource,concSource,expoRawSourcesumRemove Source columns to save memory
4BWBWSourcesumThis removes redundant columns that are not wanted in dose
5casesabscasesabsSource,populationSource,infoSource,frexposedSourcesumRemove redundant columns
6casesrrcasesrrSource,populationSource,incidenceSource,RRSourcesumRemove redundant columns
7BoDpafBoDtSource,BoDpafSourcesumRemove redundant columns

Management scenarios developed in Goherr WP3 frames the following boundaries to the use and consumption of Baltic herring and salmon as human food. Effect of these scenarios to the dioxin levels and the human food use will be evalauted quantitatively and feed into the health benefit-risk model to assess the health effect changes.

Some ideas about what kinds of objectives stakeholders may have.

  • Maximum sustainable yield.
  • Maximum production potential. (amount of fish produced in rivers to the sea)
  • Biological objective of salmon management.
  • Sustainability of salmon catch. Values behind these objectives will come from WP3 work. Objectives will be asked from the stakeholders.
  • Sustainability of herring catch --# : What is this exactly? --Jouni (talk) 07:19, 22 April 2015 (UTC)

Possible management options:

  • International agreement on fishing quota for salmon
  • Size-selective fishing of herring
  • Knowledge actions and fish recommendations
  • Agricultural policy
  • Dioxin policy

Broader scanarios considered:

  • Scenario 1: “Transformation to sustainability”
    • Hazardous substances, including dioxins, are gradually flushed out and the dioxin levels in Baltic herring are below or close to the maximum allowable level.
    • Fish stocks are allowed to recover to levels, which makes maximum sustainable yield possible and increases the total catches of wild caught fish. The catches of salmon by commercial fisheries has stabilized at low level, while the share of recreational catch increases slightly.
    • The use of the Baltic herring catch for food increases. A regional proactive management plan for the use of catch has increased the capacity of the fishing fleets to fish herring for food and through product development and joint marketing, have increased consumer demand for Baltic herring.
  • Scenario 2: “Business-as-usual”
    • The commercial catches of salmon continue to decrease. The demand for top predatory species, such as salmon and cod remains high, while the demand for herring decreased further as a result of demographic changes.
    • Most of the herring catch are used for fish meal and oil production in the region.
    • The use of Baltic herring from the southern parts of the Baltic Sea where the dioxin contents are not likely to exceed the maximum allowable level, are prioritised for human consumption. In the absence of the demand in many of the Baltic Sea countries, majority of the herring intended for direct human consumption are exported to Russia.
  • Scenario 3: “Inequality”
    • The nutrient and dioxins levels continue to decrease slowly.
    • The commercial catches of salmon have decreased further as the general attitudes favour recreational fishing, which has also resulted in decreased demand.
    • The herring catches have increased slightly, but the availability of herring suitable for human consumption remains low due to both, dioxin levels that remain above the maximum allowable limit in the northern Baltic Sea and the poor capacity to fish for food.
    • The use of the catch varies between countries. In Estonia, for example, where the whole catch has been traditionally used for human consumption, there is no significant change in this respect, but in Finland, Sweden and Denmark, herring fishing is predominantly feed directed.
  • Scenario 4: “Transformation to protectionism”
    • The level of hazardous substances also increases as emission sources are not adequately addressed.
    • Commercial salmon fisheries disappears almost completely from the Baltic Sea, although restocking keeps small scale fisheries going.
    • Many of the Baltic herring stocks are also fished above the maximum sustainable yield and total catches are declining.
    • Owing to the growing dioxin levels detected in herring, majority of the catch is used for aquaculture.


The assessment started in April 2015. The first stakeholder meeting was in February 2016. The final results with the full decision support tool was finalised in April 2018.



Value of information analyses

For detailed results, see model run on 20.4.2018. Value of information was looked at in three parts, where a bunch of similar decisions were considered together.

  • Select herring size
    • There is little expected value of perfect information (EVPI) (only 15 DALY/a) because Ban large, i.e. switching to small herring is so much better than other alternatives. This is emphasised by the fact that the expected value of including that option is 138 DALY/a.
    • If that option is excluded, EVPI increases to 68 DALY/a.
  • Consider background and limit maximal fish intake to 3 g/d are evaluated at the same time.
    • EVPI is slightly higher than with herring size, 143 DALY. This is because there is no obvious decision option to choose.
    • Dropping the option Background=No would cost 1920 DALY/a, demonstrating that that is clearly the optimal 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, 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.
    • If you always consider background intake, then the model uncertainties decrease, and your EVPI is slightly lower (134 DALY/a). When some other decision option is omitted, EVPI drops below 106 DALY/a.
  • Improved information and consumption recommendations.
    • EVPI with these decisions is 131 DALY/a, so there is some uncertainty about what to do.
    • The most important decision option is to increase information and fish availability (81 DALY/a), while any of the other options can be excluded without much change in expected value.
    • The disability weight used for tolerable daily dioxin intake is highly uncertain (hundredfold uncertainty 0.0001 - 0.01 DALY/case of exceedance). Therefore, you could expect that 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) as only 12 DALY/a. The reason for this seems to be that this disability weight rarely becomes so high that you would actually regret fish-promoting policies.


Fish is healthy food, and its use should be promoted. This applies to Baltic herring and salmon as well, even when considering the dioxin and methylmercury concentrations and vulnerable subgroups. This assessment has shown several reasons that support this conclusion:

  • Net health benefits are clear in older age groups, where the risk of cardiovascular diseases is increased.
  • Even in the subgroup of young females, the risks are close to or smaller than benefits.
  • A major health risk in this assessment is the tolerable daily intake (TDI) of dioxin. This is actually not a health risk per se, but an indicator that the exposre is approaching levels were actual health harm may occur. However, even if this is considered as a direct health risk, the previous conclusions prevail. If this outcome is ignored, the health risks become so small that there is little uncertainty about the conclusion.
  • Dioxin concentrations have decreased dramatically since the 1990's, which was the starting point of our scenarios. In fact, the decrease started even earlier during the 1970's and 1980's when industrial emissions started to improve. The current levels are roughly one tenth of the worst levels. So, the remaining dioxin problem is way smaller than its historical reputation implies.
  • Young women are the risk group but they eat less Baltic herring and salmon than other population subgroups. Therefore, fish promotion policies are likely to increase the health benefits in other subgroups (especially the elderly) much more than health risks in young women.
  • Also, when people were asked about their reactions to policies promoting or discouraging Baltic fish consumption, an interesting discrepancy was seen. Promoting policies seem to encourage people to increase their fish intake substantially. In contrast, discouraging policies were effective only in a minority, while some would paradoxically increase fish intake, and the average change would be negligible.
  • Even if the recommendations were targeted to limit Baltic herring intake in only the risk group of young women, there are probably ripple effects that would deteriorate the brand of the fish in general and thus maybe reduce fish intake in other groups as well. The other groups would benefit from fish much more than young women, and the overall health impact would be poor. (However, it should be remembered that on the one hand, people self-reported that this would not reduce their herring intake; and on the other hand, herring consumption has been decreasing for decades at the same time when discussion on dioxin risks in herring has been going on, so definitive conclusion on this point is not possible.)
  • There are still large uncertainties in both scientific and value-based issues. However, our results show that robust conclusions about decision options can be made with the current information. Also, it seems that there is no single source of additional information that would reveal crucial insights into this issue. In other words, there seems to be little or no value in postponing decision in the hope that we would, in the near future, learn something that would help us make wiser decisions.

The conclusions above are based on health considerations only. If we include economic, cultural, food security aspects into this consideretion, we can argue that:

  • The price of Baltic herring for food is clearly higher than that of herring for feed. Therefore, for fishing industry it would be beneficial to start catching more fish for human consumption and therefore effects are synergistic with those of health.
  • In many areas around the Baltic Sea, Baltic herring has high cultural value as a food and as a tradition. An increase in consumption would help maintaining the culture, and vice versa.
  • Baltic Sea could be an important source of human food, but currently it is rather a source of animal feed. If dioxin-based food regulations were abandoned, it would be easier to develop the Baltic Sea as a food reserve.

Overall, main arguments from all disciplines are in favour of getting rid of dioxin-based food restrictions related to Baltic herring and salmon, and promoting human consumption of Baltic fish.


Schematic picture of the health benefit-risk model for Baltic herring and salmon intake.
Detailed modelling diagram of the health benefit-risk model. Green nodes are original data, red nodes are based on scientific literature, and blue nodes are computational nodes. Those with a number are generic nodes designed to be used in several assessments. the number refers to the page identifier in Op_en wiki (this Opasnet wiki).


Who will be affected by the decisions?

  • Professional fishers and their organisations
  • Anglers and other recreational fishers and their organisations
  • Land owner fishers and their organisation (they have inherited rights)
  • Saami people also have inherited rights (in Sweden only?)
  • Food and fish industry.
  • Mink and fox farmers
  • All people utilising recreational values of the Baltic Sea (relates to eutrophication)
  • Farmers and agricultural sector
  • Consumers of fish
  • Producers of fish oil and fish meal
  • Baltic Sea RAC (Regional Advisory Concil) represents fishers (located in Copenhagen)
  • Hydropower plant owners

Who will affect the decisions?

  • Food safety organisations (EVIRA, Livsmedelsverket, ...)
  • Ministries (of agriculture, environment, and commerce)
  • EU: DG Mare, EU Parliament?
  • SWAM (Swedish Agency for Marine and Water Management)

Who are interested in the decisions?

  • Scientists
  • Environmental NGOs
  • Bureaucrats
  • ICES (International Council for the Exploration of the Sea)
  • Helcom


Calculation of cases of disease

Calculation of DALYs:

Model parameters

We assume that the background exposure is a uniform distribution between zero and the average Finnish intake for nutrients (according to the Finriski study). The typical nutrient intake from Baltic herring is subtracted from the average to avoid double counting.



  • Country (Denmark, Estonia, Finland, Sweden)
  • Year (current, future)
  • Gender
  • Age: 18-45 years or >45 years
  • Fish species (Baltic herring, Baltic salmon)
  • Health end-point, specified by name
  • Compound: TEQ (PCDD/F and PCB), Vitamin D, Omega3 (includes EPA and DHA), MeHg


This section will have the actual health benefit-risk model (schematically described in the above figure) written with R. The code will utilise all variables listed in the above Dependencies section. Model results are presented as tables and figures when those are available.

  • 18.5.2017: Archived exposure model Op7748/exposure by Arja (used separate ovariables for salmon and herring) [1]

Health impact model (Monte Carlo)

Model parameters

Choose which decisions to add to model (BAU of each is always considered):
Information improvements: BAU (no), yes (size:2x)
Recommendations about herring: BAU (current), eat more, eat less (size:3x)
Recommendations about salmon: BAU (current), eat more, eat less (size:3x)
Select herring size for human consumption: BAU (large only), ban large, new products (both) (size:3x)
Should background be considered? BAU (yes), no (size:2x)
Is fish consumption limited to 3 g/day? BAU (no), yes (size:2x)
Long timeline: BAU (2018), 1990, 2000, 2010 (size:4x)
Compound mixture: BAU (all), MeHg, Dioxin, Omega3 (size:4x)
Scenario for length vs TEQ (all sizes in 2009)

How many iterations to run?:

+ Show code

Exposure-response functions

  • Model run 12.4.2018 [2] 152354803523

+ Show code

Second part

+ Show code

Plot concentrations and survey

  • Requires codes Op_en7748/bayes and indirectly Op_en7748/preprocess.
  • Model run 1.3.2017 [3]

+ Show code

Sketches about modelling determinants of eating


+ Show code

Interface for BBN model

Health risk-benefit assessment model (BRA) implemented on this page produces also data for the overall Goherr Bayesian belief network model (BBN). In brief, the models are built in a way that they share the important nodes. This section describes how data from BRA is managed to fit BBN.

Data files and indices needed:

  • Consumer country
    • Country (DK, EST, FI, SWE): total population size for each country
  • Consumer gender
    • Gender (Female, Male): gender-specific number of people for each country
  • Consumer age group
    • Age (18-45, 45>): gender and age-specific number of people for each country
  • Effect of improved information
    • Information improvements (policy options to be determined)
    • Country, age, and gender-specific distributions --# : Is it realistic be so specific? --Jouni (talk) 12:47, 22 November 2017 (UTC)
  • Human consumption of salmon
    • Country, age, and gender-specific consumption (g/day)
    • The same with or without salmon recommendation policy given improved information (to be determined)
  • Human consumption of herring: same as for salmon
  • Omega3 intake from salmon and herring (mg/day)
  • Human intake of dioxin from herring
  • Human intake of dioxin from salmon
  • Dioxin intake total
  • Other intake of omega3
  • Omega3 intake total
  • Net burden of disease

+ Show code


  1. Satu Alaluusua, Pirjo-Liisa Lukinmaa, Terttu Vartiainen, Maija Partanen, Jorma Torppa, Jouko Tuomisto. (1996) Polychlorinated dibenzo-p-dioxins and dibenzofurans via mother's milk may cause developmental defects in the child's teeth. Environmental Toxicology and Pharmacology Volume 1, Issue 3, 15 May 1996, Pages 193-197. doi:10.1016/1382-6689(96)00007-5
  • Assmuth Timo and Jalonen Pauliina 2005: Risks and management of dioxin-like compounds in Baltic Sea fish: An integrated assessment. Nordic Council of Ministers, Copenhagen. Assmuth Jalonen Dioxin risk assessment 2005 [4]
  • EFSA 2012. Update of the monitoring of levels if dioxins and PCBs in food and feed. EFSA Journal 10(7):2832. doi: 10.2903/j.efsa.2012.2832



Normative scenarios
paths you need to take to reach a defined goal
Expolorative scenarios
identify key uncertainties and dependencies to describe coherent paths into the future.
Governance types
How things are managed (e.g. top down command or co-management).
Management action
Actions to be taken based on decision-maker's decision (i.e. decisions)

See also

Goherr Research project 2015-2018: Integrated governance of Baltic herring and salmon stocks involving stakeholders

GOHERR logo NEW.png Goherr public website

Workpackages including task description and follow-up:
WP1 Management · WP2 Sociocultural use, value and goverrnance of Baltic salmon and herring · WP3 Scenarios and management objectives · WP4 Linking fish physiology to food production and bioaccumulation of dioxin · WP5 Linking the health of the Baltic Sea with health of humans: Dioxin · WP6 Building a decision support model for integrated governance · WP7 Dissemination

Other relevant pages in Opasnet: GOHERR assessment · Relevant literature

Relevant data: Exposure response functions of dioxins · Fish consumption in Sweden · POP concentrations in Baltic sea fish · Exposure response functions of Omega3 fatty acids

Relevant methods: Health impact assessment · OpasnetBaseUtils‎ · Modelling in Opasnet

Relevant assessments: Benefit-risk assessment of Baltic herring · Benefit-risk assessment on farmed salmon · Benefit-risk assessment of methyl mercury and omega-3 fatty acids in fish · Benefit-risk assessment of fish consumption for Beneris · Benefit-risk assessment of Baltic herring (in Finnish)

Bonus logo.png
Eu logo.png

Related files