Difference between revisions of "Benefit-risk assessment of Baltic herring and salmon intake"
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=== Dependencies === | === Dependencies === | ||
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− | * [[ | + | '''Calculation of cases of disease |
− | * [[Goherr:_Fish_consumption_study | Consumption of fish]] | + | * totcases (Op_en2261/totcases on page [[Health impact assessment]]) with dose and RR, automatic intermediate variables |
− | * Pollutant and fatty acid | + | ** population, case-specific, from main model |
− | ** [[POPs_in_Baltic_herring | Persistent organic pollutant levels in Baltic herring]] | + | ** disincidence,Incidence of the disease of interest. Op_en5917/initiate [[Disease risk]] {{comment|# |Should we use IHME data instead?|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} |
− | ** [[POPs_in_Baltic_salmon | Persistent organic pollutant levels in Baltic salmon]] | + | *** [[Burden_of_disease_in_Finland |Burden of disease as DALY in Finland]] {{attack|# |Inactivate and merge?|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} |
− | ** [[Concentrations_of_beneficial_nutrients_in_fish | Nutrient levels in fish]] {{comment|# |Good data for Baltic herring, Salmon not taken into account yet|--[[User:Arja|Arja]] ([[User talk:Arja|talk]]) 13:27, 13 March 2017 (UTC)}} | + | ** ERF and threshold, exposure-response functions. Op_en2031/initiate [[Exposure-response function]] |
− | * | + | *** [[ERF_of_dioxin | Exposure-response functions of dioxins]] |
− | ** [[ | + | *** [[ERF_of_omega-3_fatty_acids | Exposure-response functions of fatty acids]] |
− | ** [[ | + | *** [[ERF_of_methylmercury |Exposure-response functions of methylmercury]] |
− | + | *** [[ERFs of vitamins]] {{attack|# |Has to be updated.|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} | |
− | + | ** frexposed, fraction of population that is exposed from [[Goherr: Fish consumption study]] | |
− | ** [[ | + | ** exposure, from the main model because has case-specific adjustments |
− | + | *** amount, [[Goherr:_Fish_consumption_study | Consumption of fish]] | |
+ | *** concentration, Pollutant and fatty acid concentrations in fish | ||
+ | **** [[POPs_in_Baltic_herring | Persistent organic pollutant levels in Baltic herring]] | ||
+ | **** [[POPs_in_Baltic_salmon | Persistent organic pollutant levels in Baltic salmon]] | ||
+ | **** [[Concentrations_of_beneficial_nutrients_in_fish | Nutrient levels in fish]] {{comment|# |Good data for Baltic herring, Salmon not taken into account yet|--[[User:Arja|Arja]] ([[User talk:Arja|talk]]) 13:27, 13 March 2017 (UTC)}} {{defend|# |Take data from Fineli.|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} {{comment|# |[[Omega-3 content in salmon]]: update and change the answer to point to the main page.|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} | ||
+ | **** [[Mercury concentrations in fish in Finland]] {{defend|# |update code by using Bayesian model on Kerty database.|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} | ||
+ | ***** [[Mercury and methyl mercury concentrations in fish]] {{attack|# |Inactivate.|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} | ||
+ | *** [[TEF |Toxic equivalency factor (TEF)]] {{attack|# |Create an ovariable with input string for TEF version (default: WHO2005.)|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} | ||
+ | |||
+ | '''Calculation of DALYs: | ||
+ | * totcases (see above) | ||
* [[Disability_weights | Disability weights of health effects]] | * [[Disability_weights | Disability weights of health effects]] | ||
* [[Duration_of_morbidity | Length of disease]] | * [[Duration_of_morbidity | Length of disease]] | ||
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* Country (Denmark, Estonia, Finland, Sweden) | * Country (Denmark, Estonia, Finland, Sweden) | ||
* Year (current, future) | * Year (current, future) | ||
− | * | + | * Gender |
− | * Age | + | * Age: 18-45 years or >45 years |
* Fish species (Baltic herring, Baltic salmon) | * Fish species (Baltic herring, Baltic salmon) | ||
* Health end-point (ICD-10 code?, name? something else? {{comment|# |This need to be matched for disability weight, duration of disease, background incidence and disease burden data, dose-responses|--[[User:Arja|Arja]] ([[User talk:Arja|talk]]) 09:39, 22 September 2016 (UTC)}} | * Health end-point (ICD-10 code?, name? something else? {{comment|# |This need to be matched for disability weight, duration of disease, background incidence and disease burden data, dose-responses|--[[User:Arja|Arja]] ([[User talk:Arja|talk]]) 09:39, 22 September 2016 (UTC)}} | ||
− | * Compound | + | * Compound: TEQ (PCDD/F and PCB), Vitamin D, Omega3 (includes EPA and DHA), MeHg |
=== Calculations === | === 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. | 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. | ||
− | ==== | + | ==== Exposure model ==== |
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− | + | {{comment|# |Combine this with the main model.|--[[User:Jouni|Jouni]] ([[User talk:Jouni|talk]]) 16:03, 13 April 2017 (UTC)}} | |
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<rcode name="exposure" label="Calculate dioxin and nutrient intake (for developers only)"> | <rcode name="exposure" label="Calculate dioxin and nutrient intake (for developers only)"> | ||
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objects.latest("Op_en7748", code_name = "bayes") #: pcd.pred, ans.pred, mu.pred | objects.latest("Op_en7748", code_name = "bayes") #: pcd.pred, ans.pred, mu.pred | ||
+ | #### RATHER, CREATE PCDD.CONC | ||
#### Dioxin exposure | #### Dioxin exposure | ||
+ | ############# The code below: move to EU-kalat | ||
pl <- melt(pcd.pred) | pl <- melt(pcd.pred) | ||
levels(pl$Congener) <- gsub("HCDD", "HxCDD", levels(pl$Congener)) | levels(pl$Congener) <- gsub("HCDD", "HxCDD", levels(pl$Congener)) | ||
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dioxconcsalmon <- Ovariable("dioxconcsalmon", data = dioxconcsalmon) | dioxconcsalmon <- Ovariable("dioxconcsalmon", data = dioxconcsalmon) | ||
− | tef <- opbase.data("Op_en4017.tef_values") | + | ################# Make an own code for TEF |
+ | tef <- opbase.data("Op_en4017.tef_values") #[[TEF]] | ||
tef <- Ovariable("tef", data = tef) | tef <- Ovariable("tef", data = tef) | ||
+ | ###### NO separate ovariables for salmon and herring: put them together. | ||
teqsalmon <- tef * dioxconcsalmon | teqsalmon <- tef * dioxconcsalmon | ||
teqsalmon <- aggregate(teqsalmon@output$Result, by = list(teqsalmon@output$Iter), sum) | teqsalmon <- aggregate(teqsalmon@output$Result, by = list(teqsalmon@output$Iter), sum) | ||
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teqherring <- Ovariable("teqherring", data = teqherring) | teqherring <- Ovariable("teqherring", data = teqherring) | ||
− | objects.latest("Op_en7749", code_name = "calculate_amount") # amount of salmon and herring intake | + | objects.latest("Op_en7749", code_name = "calculate_amount") # amount of salmon and herring intake [[Goherr: Fish consumption study]] |
expoherring <- teqherring * amountHerring | expoherring <- teqherring * amountHerring | ||
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expodiox <- exposalmon + expoherring | expodiox <- exposalmon + expoherring | ||
+ | ############## UPDATE | ||
objects.latest("Op_en1838", code_name = "bayes") #nutrient concentrations | objects.latest("Op_en1838", code_name = "bayes") #nutrient concentrations | ||
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# Make the background exposure uncertain rather than an index. | # Make the background exposure uncertain rather than an index. | ||
+ | #################### USE collapseMarginal instead. Produces ovariable expo.add | ||
background <- Ovariable( | background <- Ovariable( | ||
output = data.frame( | output = data.frame( | ||
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addexposure <- addexposure * background | addexposure <- addexposure * background | ||
− | # This should be done in data already? Background compatibility? | + | # This should be done in data already? Background compatibility? #### YES DO IN DATA |
colnames(addexposure@output)[1:2] <- c("Background", "Gender") | colnames(addexposure@output)[1:2] <- c("Background", "Gender") | ||
levels(addexposure@output$Gender) <- c("Male", "Female") | levels(addexposure@output$Gender) <- c("Male", "Female") | ||
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exposure <- exposure + addexposure | exposure <- exposure + addexposure | ||
+ | ################## CREATE a separate ovarible about children's exposure: expo.child | ||
# Convert mother's dioxin intake (pg/d) into child's dioxin concentration (pg/g) in fat after 6 months of breast-feeding. | # Convert mother's dioxin intake (pg/d) into child's dioxin concentration (pg/g) in fat after 6 months of breast-feeding. | ||
# For details, see [[ERF of dioxin#Dental defects]] | # For details, see [[ERF of dioxin#Dental defects]] | ||
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# Väkimäärä. TÄTÄ KÄYTETÄÄN disincidence-ovariablen suhteuttamisessa CHD:n suhteen. | # Väkimäärä. TÄTÄ KÄYTETÄÄN disincidence-ovariablen suhteuttamisessa CHD:n suhteen. | ||
− | + | ######################## NOT SURE THIS IS THE BEST WAY | |
#!!+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ | #!!+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ | ||
pop <- opbase.data("Op_en2949") # [[Population of Finland]] | pop <- opbase.data("Op_en2949") # [[Population of Finland]] | ||
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# Drop ERF rows that are not used in this assessment. | # Drop ERF rows that are not used in this assessment. | ||
− | + | #################### NOT SURE THERE IS REASON TO REMOVE | |
erfpois <- paste(ERF@data$Exposure_agent, ERF@data$Trait, ERF@data$ERF_parameter, ERF@data$Scaling) %in% | erfpois <- paste(ERF@data$Exposure_agent, ERF@data$Trait, ERF@data$ERF_parameter, ERF@data$Scaling) %in% | ||
c( | c( | ||
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# Drop nuisance indices because they use a lot of memory in oapply. | # Drop nuisance indices because they use a lot of memory in oapply. | ||
+ | ################### SHOULD NOT USE A LOT OF MEMORY WITH aggregate-based oapply. | ||
ERF@output <- ERF@output[ERF@output$Age != "<14" , ] | ERF@output <- ERF@output[ERF@output$Age != "<14" , ] | ||
threshold@output <- threshold@output[threshold@output$Age != "<14" , ] | threshold@output <- threshold@output[threshold@output$Age != "<14" , ] | ||
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######################################## Tautiriski | ######################################## Tautiriski | ||
+ | ################################### MAKE A SINGLE DISINCIDENCE OVARIABLE FROM THE CODE BELOF UNTIL HIA. | ||
#!!++++++++++++++++++++++++++++++++++++++++++++++++++ | #!!++++++++++++++++++++++++++++++++++++++++++++++++++ | ||
objects.latest("Op_en5917", code_name = "initiate") # [[:op_en:Disease risk]] ovariable disincidence | objects.latest("Op_en5917", code_name = "initiate") # [[:op_en:Disease risk]] ovariable disincidence |
Revision as of 16:03, 13 April 2017
This page is a assessment.
The page identifier is Op_en7748 |
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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 (year 2020?)
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
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
- totcases (Op_en2261/totcases on page Health impact assessment) with dose and RR, automatic intermediate variables
- population, case-specific, from main model
- disincidence,Incidence of the disease of interest. Op_en5917/initiate Disease risk --# : Should we use IHME data instead? --Jouni (talk) 16:03, 13 April 2017 (UTC)
- Burden of disease as DALY in Finland ⇤# : Inactivate and merge? --Jouni (talk) 16:03, 13 April 2017 (UTC)
- ERF and threshold, exposure-response functions. Op_en2031/initiate Exposure-response function
- Exposure-response functions of dioxins
- Exposure-response functions of fatty acids
- Exposure-response functions of methylmercury
- ERFs of vitamins ⇤# : Has to be updated. --Jouni (talk) 16:03, 13 April 2017 (UTC)
- frexposed, fraction of population that is exposed from Goherr: Fish consumption study
- exposure, from the main model because has case-specific adjustments
- amount, Consumption of fish
- concentration, Pollutant and fatty acid concentrations in fish
- Persistent organic pollutant levels in Baltic herring
- Persistent organic pollutant levels in Baltic salmon
- Nutrient levels in fish --# : Good data for Baltic herring, Salmon not taken into account yet --Arja (talk) 13:27, 13 March 2017 (UTC) ←# : Take data from Fineli. --Jouni (talk) 16:03, 13 April 2017 (UTC) --# : Omega-3 content in salmon: update and change the answer to point to the main page. --Jouni (talk) 16:03, 13 April 2017 (UTC)
- Mercury concentrations in fish in Finland ←# : update code by using Bayesian model on Kerty database. --Jouni (talk) 16:03, 13 April 2017 (UTC)
- Mercury and methyl mercury concentrations in fish ⇤# : Inactivate. --Jouni (talk) 16:03, 13 April 2017 (UTC)
- Toxic equivalency factor (TEF) ⇤# : Create an ovariable with input string for TEF version (default: WHO2005.) --Jouni (talk) 16:03, 13 April 2017 (UTC)
Calculation of DALYs:
- totcases (see above)
- Disability weights of health effects
- Length of disease
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 (ICD-10 code?, name? something else? --# : This need to be matched for disability weight, duration of disease, background incidence and disease burden data, dose-responses --Arja (talk) 09:39, 22 September 2016 (UTC)
- 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.
Exposure model
--# : Combine this with the main model. --Jouni (talk) 16:03, 13 April 2017 (UTC)
Health impact model (Monte Carlo)
- Model run 13.3.2017: a simple copy of op_fi:Silakan hyöty-riskiarvio [1]
- Model run 13.3.2017 with showLocations function [2]
- Model run 13.3.2017 produces totcases results but are not meaningful yet [3]
- Model run 14.3.2017 with exposure graph [4]
- Model run 14.3.2017 bugs not fixed [5]
Plot concentrations and survey
- Requires codes Op_en7748/bayes and indirectly Op_en7748/preprocess.
- Model run 1.3.2017 [6]
References
Keywords
See also
- Risk and Benefit Assessment of Herring and Salmonid Fish from the Baltic Sea Area
- Swedish Market Basket 2010
- Riksmaten 2010
- Danskernes kostvaner 2011-2013