Benefit-risk assessment of Baltic herring and salmon intake

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

Assessment presentation · show ready-made model results (without salmon)

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Scope

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.

Question

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.

Participants

  • National institute for health and welfare (THL)
  • Goherr project group

Boundaries

  • 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)

Decisions and scenarios

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.

  • 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.

Timing

  • Model development during 2016 and 2017
  • First set of results in March 2017, draft publication in March 2018

Answer

This section will be updated as soon as preliminary results are available

Results

Conclusions

Rationale

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).

Stakeholders

  • Policy makers
    • Food safety authorities
    • Fisheries management
  • Researchers
    • Food safety
    • Health
  • NGO's
    • WWF
    • Active consumers
    • Marine Stewardship Council
  • Baltic sea fishers and producers?

Dependencies

Calculation of cases of disease

Calculation of DALYs:

Decisions(-)
ObsDecision makerDecisionOptionVariableCellChangeResultDescription
1Food safety authorityBackgroundYesbgexposureIdentityConsider background from other sources
2Food safety authorityBackgroundNobgexposureReplace0Do not consider background from other sources
Background exposure(-)
ObsCountryGenderExposure_agentResultUnitDescription
1FIMaleVitamin D11.7µg /dFinriski 12 - 0.3 silakasta
2SWEMaleVitamin D11.7µg /dFinriski 12 - 0.3 silakasta
3ESTMaleVitamin D11.7µg /dFinriski 12 - 0.3 silakasta
4DKMaleVitamin D11.7µg /dFinriski 12 - 0.3 silakasta
5FemaleVitamin D8.5µg /dFinriski 8.7 - 0.2 silakasta
6MaleEPA120mg /dFinriski 125 - 4.6 silakasta
7FemaleEPA96mg /dFinriski 100 - 3.9 silakasta
8MaleDHA118mg /dFinriski 125 - 6.7 silakasta
9FemaleDHA94mg /dFinriski 100 - 5.4 silakasta
10PCDDF0pg /d (TEQ)
11PCB0pg /d (TEQ)
12MeHg0µg /d
13logTEQ0log(pg /g)
Exposure-response functions of interest(-)
ObsExposure_agentRespResponseER_functionScalingDummy
1TEQTooth defectYes or no dental defectERSNone1
2TEQCancerCancer morbidityCSFBW1
3TEQDioxin TDIDioxin recommendation tolerable daily intakeTDIBW1
4DHAChild's IQLoss in child's IQ pointsERSNone1
5Omega3Heart (CHD)CHD2 mortalityRelative HillNone1
6Omega3StrokeStroke mortalityRelative HillNone1
7Vitamin DVitamin D intakeVitamin D recommendationStepNone1
8MeHgChild's IQLoss in child's IQ pointsERSBW1
DALYs of responses(DALY /case)
ObsRespDALYDescription
1Heart (CHD)5 - 15Assumes DW 1 and D 10 U 50%
2Stroke5 - 15Assumes DW 1 and D 10 U 50 %
3Tooth defect0 - 0.12DW 0.001 D 60 U 100 %. Or should we use this: Developmental defect: caries or missing tooth, 0.008 (0.003 - 0.017), Periodontitis weight from IHME. D: 1. U from IHME?
4Cancer0 - 0.28DW 0.1 D 20, in addition loss of life expectancy 5 a. This comes from a lifetime exposure, so it is (linearly( assumed that 1/50 of this is caused by one-year exposure. U 100 %
5Vitamin D intake0.0001 - 0.0101DW 0.001 D 1 U 101x. 1 if not met
6Dioxin TDI0.0001 - 0.0101DW 0.001 D 1 U 101x. 1 if not met
7Child's IQ0.0517 (0.03 - 0.0817)Intellectual disability, mild (IQ<70): 0.031/IQ point (0.018-0.049) From IHME. D 50 U from IHME.
DW = disability weight
D = duration (a)
U = uncertainty
Diox conc fishing areas(TEQ)
ObsAreaFishResultConcentrations used for countries
124Herring3.08DK
225-29Herring1.95SE
328Herring2.84
430-31Herring2.29FI (reference: reflects EU-kalat study)
532Herring2.45EE
624Salmon16.0DK
725-29Salmon10.9
828Salmon10.9
930-31Salmon 9.3FI, SE (reference: reflects EU-kalat study)
1032Salmon10.7EE

PCDD/F and PCB concentration distributions for each fish species and country are estimated in the following way:

  • 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 above).
  • 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. --# : It should be checked how realistic assumption this is. --Jouni (talk) 13:40, 10 October 2017 (UTC)
Landing of fish from different areas in Baltic Sea by country.
Fish species and area Country
DK FI EE SE
Tot herring (1000t) 4.8 132.4 35.3 66.5
Total salmon (t) 122 367 9 315
Herring 24 73 % 1 %
Herring 25-29 6 % 20 % 21 % 76 %
Herring 28.1 47 %
Herring 30 73 % 21 %
Herring 31 3 % 0 %
Herring 32 0 % 3 % 33 % 0 %
Salmon 25-29 7 % 11 % 6 %
Salmon 30-31 78 % 94 %
Salmon 32 15 % 67 % 0 %
Salmon 28 22 %
Salmon 24 92 %
ICES subdivisions
Subdivision Name
21 Kattegat
22 Great Belt
23 Öresund
24 Baltic West of Bornholm
25 Southern Central Baltic West
26 Southern Central Baltic East
27 North West of Gotland
28 Eastern Main Basin
28.1 Gulf of Riga
28.2 Eastern Main Basin
29 Åland Sea
30 Bothnian Sea
31 Bothnian Bay
32 Gulf of Finland
Number of samples in EU-kalat study for PCDD/F and PCB measurements.
Catch location Subdivision Fish_species Number of samples
Hanko 29 Small Baltic herring (< 17 cm) 2
Kotka 32 Small herring 2
Oulu 31 Small herring 2
Pori 30 Small herring 32
Turku 29 Small herring 2
Vaasa 30 Small herring 2
Hanko 29 Large Baltic herring (>= 17 cm) 3
Kotka 32 Large herring 3
Oulu 31 Large herring 2
Pori 30 Large herring 42
Turku 29 Large herring 3
Vaasa 30 Large herring 3
Hanko 29 Salmon 1
Kotka 32 Salmon 2
Oulu 31 Salmon 2
Pori 30 Salmon 2
Turku 29 Salmon 2

Analyses

Indices

  • 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

Calculations

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 run 13.3.2017: a simple copy of op_fi:Silakan hyöty-riskiarvio [2]
  • Model run 13.3.2017 with showLocations function [3]
  • Model run 13.3.2017 produces totcases results but are not meaningful yet [4]
  • Model run 14.3.2017 with exposure graph [5]
  • Model run 14.3.2017 bugs not fixed [6]
  • Model run 30.5.2017 [7]
  • Model run 12.6.2017 with 2D Monte Carlo [8]
  • Model run 8.9.2017 with known bugs fixed [9]
  • Model run 6.10.2017: added updated mc2d function, better exposure$Exposure (To eater or To child), Background as marginal after mc2d, MeHg concentrations; bugs fixed with conc_mehg and IQ disabilityweight [10]
  • Model run 6.10.2017: 1000 iterations [11]
  • Model run 11.10.2017: country-specific concentrations [12]
  • Model run 12.10.2017: Background bug fixed [13] objects.get("150780268107")
  • Model run 12.10.2017: with marginal background and new Limit decision [14] objects.get("150783160307")
  • Model run 19.10.2017: n = 2117 and mc2d$run2d = FALSE [15]
  • Model run 27.10.2017: salmon removed from amount. [16]
  • Model run 15.11.2017: salmon included [17]

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Second part

  • Model run 4.6.2017 [18]
  • Model run 11.6.2017 with 2D Monte Carlo [19]
  • Model run 6.10.2017 [20] barchart shows blocks wrong in Opasnet but correctly on own computer
  • Model run 12.10.2017 [21]
  • Model run 16.10.2017: ggplot objects stored [22]

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Plot concentrations and survey

  • Requires codes Op_en7748/bayes and indirectly Op_en7748/preprocess.
  • Model run 1.3.2017 [23]

+ Show code

References


Keywords

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)

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