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

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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 [4].

Title page

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

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.

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 Authority. 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.

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.

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 exceeding 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.

Keywords

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

Background

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.

Methods

   the aim, design and setting of the study
   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

Modelling

The overall aim of the study was to estimate health risks and benefits of important compounds (dioxins, dioxin-like PCBs, methylmercury, omega-3 fatty acids, and vitamin D) found in Baltic herring and salmon at current consumption levels. The assessment model was implemented in an open and modular way at Opasnet web-workspace. In practice, this means that all the data and code used for different parts, or modules, of the model are located on different pages at Opasnet. These pages are called knowledge crystals, as their structure and workflow follow certain rules (Tuomisto et al 2018, forthcoming). In this section, we give an overview of the model. Links to the module pages and all details can be found from the assessment page http://en.opasnet.org/w/Goherr_assessment. The whole model with data and codes is also available at IDA research data repository. #### IDA URL NEEDED!^a

The benefit-risk assessment was based on a modular Monte Carlo simulation model, which had a hierarchical Bayesian module for estimating dioxin concentrations. The input distributions were derived either directly from data or from scientific publications. If no published information was available (as was the case with e.g. disability weights for non-typical endpoints such as tolerable weekly intakes or infertility, we used author judgement and wide uncertainty bounds (these judgements are described later in the text). The model was run with 5000 iterations using R statistical software (version 3.5.1, https://cran.r-project.org).

Consumption survey

A questionnaire survey was done to study consumer’s fish-eating habits in four Baltic Sea countries (Finland, Sweden, Estonia, and Denmark) 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).

Based on random sampling (with replacement) of the survey results, distributions of individual long-term fish consumption (in grams per day) were estimated in subgroups defined by country, gender, and age. In addition, people's reactions to several policies were predicted based on their answers (e.g. what if fish consumption is recommended or restricted; what if the availability and usability of these species improves; what if the price of fish changes). These decision scenarios were used to alter the business as usual scenario and compare results between scenarios. 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 versus 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.

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.

Concentrations

Fish-size-specific PCDD/F and dioxin-like PCB concentration distributions for each fish species and country were estimated based on EU Fish II study. 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. A hierarchical Bayesian module was developed with the JAGS package of R software. The model assumed ca. 7 per cent annual decrease in dioxin concentrations, based on long time trends measured in Finland. The samples were caught between 2009 and 2010.

The concentrations in Baltic herring were found out to be highly sensitive to fish size, while size-dependency was much weaker in salmon. Herring sizes and dioxin concentrations in different scenarios came from a fish growth model developed by SLU in BONUS GOHERR project (Gårdmark et al, forthcoming).

The fish samples came mostly from the Bothnian Sea, which is an important area for Finnish and Swedish catch. The concentrations distributions for the studied countries ware derived from the concentration model results by scaling them with the average concentration on a catch area of interest relative to the average from Bothnian Sea. 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.

arg8317: . Fix the claim to the Goherr assessment that small and large herring were treated as separate species! --Jouni (talk) 05:46, 20 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

Concentrations were weighted and summed up to toxic equivalency quantities (TEQ) by using WHO 2005 toxic equivalency factors (TEF). Levels of fatty acids and vitamin D in Baltic herring were based on measured data obtained from the Finnish Food Safety Authority, and those in salmon are based on scientific literature. Methylmercury concentrations were based on Kerty database produced by the Finnish Environment Institute.

Exposure-responses

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 dioxin and methylmercury during pregnancy and breast-feeding, as they were derived from the mother's exposure using simple toxicokinetic models. In the default scenario, nutrients were assumed to have an uncertain background intake from other sources; this was relevant for non-linear exposure-response function, in practice leading to a diminished health benefit of fish consumption.

Exposure-response functions were derived for several pairs of exposure agents and responses (see Table 1). We derived the exposure-response functions for infertility and tooth defects indirectly from published results, so the rational of those endpoints is described here in more detail.

Table 1. Exposure-response functions used in the assessment.

Exposure agent	Response	Esposure-response unit	Exposure-response function	References
TEQ (intake through placenta and mother's milk)	male infertility due to sperm concentration decrease	pg /g in boy's body fat	linear; slope 0.00006+-0.00004 (mean+-sd)	mother's exposure must be converted to child's exposure (measured as pg /g fat)
TEQ (intake through placenta and mother's milk)	developmental dental defects	log (pg /g) in child's body fat	linear; slope 0.26 +- 0.12 (mean+-sd)	epidemiological study in Finland
TEQ	cancer morbidity	pg/kg/day	linear; slope with triangular distribution 0.000032, 0.000035, 0.000156	U.S.EPA dioxin risk assessment with a sensitive cancer response (to avoid underestimation).
TEQ	current EFSA dioxin recommendation: tolerable daily intake	pg/kg/week	acceptable range 0 - 14	EC Scientific Committee on Food recommendation
TEQ	suggested EFSA dioxin recommendation: tolerable daily intake	pg/kg/week	acceptable range 0 - 2
omega-3 fatty acids	coronary heart disease mortality	mg/day	ED50: -0.17 (-0.25 - -0.088) (mean, 95 % confidence interval)	A previous risk assessment
omega-3 fatty acids	stroke mortality	mg/day	ED50: -0.12 (-0.25 - 0.01) (mean, 95 % confidence interval)	a previous risk assessment
vitamin D	vitamin D recommendation	µg/day	acceptable range 0 - 100	a step function based on the daily intake recommendations for adults in Finland
methylmercury	loss in child's IQ points	mg/kg/day	linear; slope 6.533 (0 - 14) (mean, 95 % confidence interval)	a previous risk assessment.
DHA	loss in child's IQ points	mg/day	linear; slope -0.0013 (-0.0018 - -0.0008) (mean, 95 % confidence interval)	a previous risk assessment.

In humans, sperm concentrations have been shown to decrease permanently if boys are exposed to dioxins before nine years of age. The results come from Seveso and a Russian children's study.

EFSA recently assessed this risk from the Russian children's study and concluded that significant effect was seen already in the second quartile with median PCDD/F TEQ concentration 10.9 pg/g fat, when measured from the serum of the boys at the age of ca. 9 years. Mean sperm concentration was ca. 65 (95 % CI 50-80) million/ml in the lowest quartile, while in all other quartiles the concentration was ca. 40 (95 % CI 30-55) million/ml. Due to the shape of the effect, we used a non-linear exposure-response curve with half of the maximum effect (effective dose 50, ED50) occurring at TEQ concentration 10 pg/g fat.

However, sperm concentration as such is not an adverse health effect. It only manifests itself if the concentration is low enough to prevent conception in a reasonable time window, say, five years. According to a review, the success rate of couples who try to get pregnant is 65 % in 6 months if the sperm concentration is above 40 million/ml. Below that concentration, the probability is fairly proportional to the sperm concentration.

Based on this, we estimated that (assuming independent probabilities between 6-month periods), the probability of not getting pregnant in five years follows this curve:

P(infertility after 5 a) = (1 - 0.65 (1+ (-0.39c}{c + 10 pg/g}))^10

where c is the dioxin concentration in boy's fat tissue. This curve is pretty linear below TEQ concentration 50 pg/g with slope ca. 0.00006 g/pg, meaning that for each 1 pg/g increase in dioxin concentration the boy's fat tissue (or serum fat), there is an incrementally increased probability of 0.00006 that he cannot get a child even after five years of trying.

Exposure-response function for tooth defect was also derived from several studies. Alaluusua and coworkers have studied dioxin exposure in small children and the development of permanent molar teeth. They have found defects in both general population in Finland from the exposures in the 1980's and children exposed during the Seveso accident

Based on these studies, we approximated that the effect is linearly correlated with the logarithm of the dioxin concentration in the child.

Disease burden

Background disease levels were needed for stroke and cardiovascular diseases and were obtained from The Institute for Health Metrics and Evaluation (IHME).

Disease burden was estimated in two alternative ways: if the burden of a particular disease in the target population was known, the attributable fraction of a particular compound exposure was calculated. If it was not known, the attributabe number of cases due to the exposure was estimated, and this was multiplied by the years under disease per case and the disability weight of the disease (Table 2.). If the exposure-response function was relative to background risk of the disease, disease risks 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.

The durations of diseases were based on our general understanding of pathological progress of these diseases rather than direct epidemiological evidence. We tried to be realistic with estimates but also not to underestimate the risks of fish consumption, so that potential conclusions about safety of fish would not be unfounded.

With the non-typical health effects, namely exceedances of tolerable weekly intakes and deviation from the vitamin D recommendation, we used very wide uncertainty distributions, as it was unclear how much weight should be given to endpoints that are only indications of potantial health risk. A value of information analysis was performed to test the importance of these uncertainties.

Childlessness can be viewed as tragedy of life, so the disability weight could be in the order of 0.1 DALY per year permanently (50 years). However, the disability weight applies to only half of the children (boys), and we can fairly assume that half of the couples get a satisfactory solution via adoption, in-vitro fertilisation or other treatments. Therefore, the impact is 0.1*50*0.5*0.5 DALY/case = 1.25 DALY/case, with rather high uncertainty (say, 0-2.5 DALY/case).

Table 2. Disability-adjusted life years (DALY = disability weight * duration) per case of health impact

Response	DALYs per case	Description
coronary heart disase mortality	5 - 15	disability weight 1 and duration 10 a, with 50% uncertainty
stroke mortality	5 - 15	disability weight 1 and duration 10 a with 50 % uncertainty
tooth defect	0 - 0.12	disability weight 0.001 and duration 60 a with 100 % uncertainty.
cancer	0 - 0.28	disability weight 0.1 and duration 20 a, and 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. With 100 % uncertainty
vitamin D intake	0.0001 - 0.0101	disability weight 0.001 and duration 1 a with 100-fold log-uniform uncertainty
dioxin TWI	0.0001 - 0.0101	disability weight 0.001 and duration 1 a with 100-fold log-uniform uncertainty
TWI 2018	0.0001 - 0.0101	disability weight 0.001 and duration 1 a with 100-fold log-uniform uncertainty
infertility	0-2.5	disability weight and duration 50 a with two-fold uncertainty. See also text.
child's IQ	0.0517 (95 % CI 0.03 - 0.0817)	Intellectual disability, mild (IQ<70) has disability weight 0.031 (95 % CI 0.018-0.049) based on Institute for Health Metrics and Evaluation, Seattle. This is scaled to one IQ point with duration 50 a.

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.

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Figure 1. Cumulative concentration distributions of the four key exposure agents in Baltic herring and salmon. For dioxin, also the time trend since 1990 is shown.arg3605: . Leave only four agents: Omega3, vitamin D, methylmercury, and TEQ. --Jouni (talk) 21:15, 21 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

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Figure 2. Cumulative fish consumption distributions of Baltic herring and salmon in different subgroups of the studied countries.

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Figure 3. Cumulative dioxin exposure distributions shown by subgroup and country.arg6931: . Change these from TDI to TWI and convert to per kg. And add new TWI line. --Jouni (talk) 06:29, 19 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

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Figure 4. Individual change in consumption after a recommendation to either increase or reduce fish intake is given.arg3605: . Make a new graph with max 10 g/d. --Jouni (talk) 21:15, 21 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

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Figure 5. Disease burden of eating Baltic fish in Denmark, Estonia, Finland, and Sweden (expected value on the individual level). Note that negative values mean improved health. mDALY: 0.001 disability-adjusted life years. CHD: coronary heart disease, IQ: intelligence quotient, TWI: tolerable weekly intake. arg6931: . Remove policy "inconsistent". TDI --> TWI 2001. Add TWI 2018.Order: DK; EST, FI; SWE. Title: Disease burden of Baltic fish by country, group, and policy. Countries on columns, policies on rows. --Jouni (talk) 06:29, 19 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

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Burden of disease of the most important environmental health factors in Finland. BONUS GOHERR results are from this study, others from a previous publication..

Concentration distributions of the key exposure agents in Baltic herring and salmon are shown in Figure 1. In general, Baltic herring has lower concentrations than salmon, but for vitamin D the levels in salmon are lower. Dioxin concentrations have reduced a lot since 1990. The same trend has existed since the 1970's (data not shown).

Fish consumption varies a lot between countries and population subgroups (Figure 2.). Only about a quarter of people report wild Baltic salmon consumption at all. Many people also say that they do not know where their salmon comes from and whether it is salmon or rainbow trout. Landing statistics imply that the consumption of wild Baltic salmon is actually lower than reported (data not shown).

Herring consumption is more accurately known, although the Danes are not sure whether their herring comes from the Baltic Sea or the North Sea. There is large individual variation (almost hundredfold) in fish consumption in most subgroups.

There is also large variation among population subgroups. Estonians eat clearly more Baltic herring and Danes eat less than other countries. Males tend to eat more, and young people eat less than other population subgroups. These differences are rather similar in all countries, although at different levels. The fraction of people that do not eat Baltic herring at all varies a lot between subgroups: it is only 25 % in old male Estonians, while it is more than 90 % in young female Danes. There is also a sizable fraction who eat Baltic herring more than 10 g/day. This varies from a few percent in young people to up to ca. 30 % in old Estonians.

Because of the large variation in fish consumption, also the dioxin exposure varies more than hundred-fold within population subgroups (Figure 3.). The variation between subgroups is also large. In the model, many people have apparent zero exposure because other dioxin sources than Baltic fish were not included. A fraction from a few percent to a quarter exceed the Scientific Committee for Food TWI value from 2001. The fraction is much higher, from 20 to up to 75 %, when the new EFSA TWI value of 2 pg/kg/week from 2018 is used as the criterion. arg3605: . Change the name to TWI 2001 and TWI 2018? --Jouni (talk) 21:15, 21 November 2018 (UTC) (type: truth; paradigms: science: relevant attack)

We also asked in the questionnaire, how the respondent would change fish intake if an increase or decrease was recommended (Figure 4.). The outcome depends on previous consumption but not much on population subgroup. If increase is recommended, a clear and systematic increase is seen in responses. In contrast a recommendation to reduce intake results in inconsistent effects. Some people obey the recommendation, but almost an equal amount does the opposite, and most do not change fish intake. This phenomenon is seen already at current intake levels below 5 g/day, where most of the population is.

The main objective of this study was to compare health risks and benefits of Baltic fish consumption. Figure 5. shows large variation between population subgroups. The most dominant feature is that the cardiovascular benefits in old age groups clearly dominate all risks. This is even more pronounced if Baltic fish is considered as the primary source of omega-3 fatty acids and thus have larger marginal benefits (data not shown); in the default assessment other sources are considered primary.

Health impacts overall are much smaller in young age groups, and in women the critical issues are effects on child's intelligence quotient (IQ), tooth defects, and sperm concentration, not the health impacts to the woman herself. These risks are in the same range as the health benefits, so the overall balance depends on the disability weights of distinct outcomes and which of them to choose (sperm concentration change is a single response but can be measured with three alternative metrices: infertility, TWI 2001, and TWI 2018).

The policy of recommending increased consumption seems to have only a minor effect. In contrast, a recommended consumption reduction does not show on the graph at all. This illustrates that dioxin policies are more effective when implemented on emission reduction, as that has reduced the dioxin exposures and thus risk effectively during the last 40 years.

In a bigger picture, Baltic fish and its health hazards are only one of the many environmental health risks (Figure 6.). It is not even close to the largest ones (which are in the order of tens of thousands DALY), but it may be in the top 10 list.

It is possible that we are overoptimistic about the current sperm concentrations, as reduction from subfertile levels could increase the probability of infertility more than our model predicts. So, we did a sensitivity analysis with men that have already decreased sperm concentrations from an unrelated reason. Dioxins are likely to reduce that even further. For example, if the sperm concentration is 10 million/ml, the probability of infertility in five years is 0.32 based on the equation above. That increases to 0.48 at dioxin concentration 100 pg/g. This exposure-response is non-linear, with half of the effect occurring already at 10 pg/g. If ten percent of the population had such low semen concentration and if 20 % of boys exceed 10 pg/g (as seems to be the case according to our model), then we would see for example in Finland 25000 boys/year * 0.1 with low fertility * 0.2 with high dioxin * 0.08 absolute increase in infertility = 40 cases per year, each 1.25 DALY and thus 50 DALY in total. This is clearly more than the 8 DALY from the default model, but both are negligible in Figure 6 where any impacts below 100 DALY are barely visible. They are also much smaller than the 25000 boys/year * 0.1 with low fertility * 0.32 absolute probability of infertility * 1.25 DALY = 1000 DALY due to infertility from all other causes of low sperm concentration.

Value of information (VOI) was looked at for specific decision scenarios, where a bunch of similar decisions were considered together. In these VOI analyses, infertility was used as the outcome for the sperm concentration effect, while tolerable weeksly intakes (both the current "Dioxin TWI" and the new suggested "TWI 2018") were ignored.

Value of information was calculated for the total burden of disease in a random population subgroup in the four study countries, but using uncertainties for individual people. This approach ensures that value of information is not underestimated, because at population level many uncertainties are smaller than at individual level.

Decision about selecting herring size has practically no expected value of perfect information (EVPI) (only 1.5 DALY/a) because Ban large, i.e. switching to small herring is in most cases better than other alternatives.

Decision about improved information (including availability and usability of fish) and consumption recomas mendations has EVPI with these decisions of 40 DALY/a, so there is some uncertainty about what to do. The most important decision option is to increase information and fish availability (145 DALY/a), while any of the other options can be excluded without much change in expected value.

Discussion

This section should discuss the implications of the findings in context of existing research and highlight limitations of the study.

Dioxin and PCB concentrations have been constantly decreasing in Baltic fish for 40 years, and now they are mostly below EU limits. Also Baltic herring consumption has been decreasing during the last decades and is now a few grams per day, varying between age groups (old people eat more), genders (males eat more) and countries (Estonians eat more and Danes less than others). People reported that better availability of easy products, recipes, and reduced pollutant levels would increase their Baltic herring consumption. In contrast, recommendations to reduce consumption would have little effect on average.

Health benefits of Baltic herring and salmon clearly outweigh health risks in age groups over 45 years. Benefits are higher even in the most sensitive subgroup, women at childbearing age. The balance is close to even, if exceedance of the tolerable daily intake is given weight in the consideration and if other omega-3 sources are given priority over fish. The analysis was robust in a sense that we did not find uncertainties that could remarkably change the conclusions and suggest postponing decisions in hope of new information.

The very recent EFSA TWI recommendation for dioxin (2 pg/kg/week as compared with the previous TWI 14 pg/kg/week) dramatically increases the fraction of non-compliant population in all countries studied. However, the implications of this fact are far from clear and require further discussion.

First, the most sensitive outcome, namely sperm concentration decrease, is only relevant for young women who are planning to have children. Should this value be applied to all population subgroups?

Second, as dioxin exposure strongly relates to otherwise healthy Baltic fish (especially Baltic herring) in the Nordic countries, should these health benefits be considered when dioxin policy is designed?

Third, Baltic herring has also other important values: economical (Baltic herring has the largest share of the landing of Baltic fish) , ecological (sustainable yield is large and catch removes nutrients from the sea), climate (Baltic herring could replace cattle and other climate-unfriendly food sources), social (herring is cheap and easy food), and cultural (Baltic herring is an important part of coastal culture). Should these values be considered when dioxin policy is designed?

This study was not designed to answer these value-based questions. But it is useful to understand that the remaining scientific uncertainties about dioxin risks are low, and the critical questions are these just mentioned. Political discussion and deliberation is needed, and the scientific facts are crucial elements in that discussion.

Conclusions

This should state clearly the main conclusions and provide an explanation of the importance and relevance of the study reported.

List of abbreviations

CHD: coronary heart disease

CI: confidence interval

DALY: disability-adjusted life year

DHA: docosahexaenic acid

ED50: effective dose 50

EFSA: European Food Safety Authority

EPA: eicosapentaenic acid

EVPI: expected value of perfect information

IQ: intelligence quotient

TEF: toxic equivalency factor

TEQ: toxic equivalency quantity

VOI: value of information

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).

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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

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Wyllie AH, Kerr JFR, Currie AR. Cell death: the significance of apoptosis. In: Bourne GH, Danielli JF, Jeon KW, editors. International review of cytology. London: Academic; 1980. p. 251-306.

OnlineFirst chapter in a series (without a volume designation but with a DOI)

Saito Y, Hyuga H. Rate equation approaches to amplification of enantiomeric excess and chiral symmetry breaking. Top Curr Chem. 2007. doi:10.1007/128_2006_108.

Complete book, authored

Blenkinsopp A, Paxton P. Symptoms in the pharmacy: a guide to the management of common illness. 3rd ed. Oxford: Blackwell Science; 1998.

Online document

Doe J. Title of subordinate document. In: The dictionary of substances and their effects. Royal Society of Chemistry. 1999. http://www.rsc.org/dose/title of subordinate document. Accessed 15 Jan 1999.

Online database

Healthwise Knowledgebase. US Pharmacopeia, Rockville. 1998. http://www.healthwise.org. Accessed 21 Sept 1998.

Supplementary material/private homepage

Doe J. Title of supplementary material. 2000. http://www.privatehomepage.com. Accessed 22 Feb 2000.

University site

Doe, J: Title of preprint. http://www.uni-heidelberg.de/mydata.html (1999). Accessed 25 Dec 1999.

FTP site

Doe, J: Trivial HTTP, RFC2169. ftp://ftp.isi.edu/in-notes/rfc2169.txt (1999). Accessed 12 Nov 1999.

Organization site

ISSN International Centre: The ISSN register. http://www.issn.org (2006). Accessed 20 Feb 2007.

Dataset with persistent identifier

Zheng L-Y, Guo X-S, He B, Sun L-J, Peng Y, Dong S-S, et al. Genome data from sweet and grain sorghum (Sorghum bicolor). GigaScience Database. 2011. http://dx.doi.org/10.5524/100012.

Figures, tables and additional files

See General formatting guidelines for information on how to format figures, tables and additional files.

See also

• Swedish Food Safety Authority about EFSA dioxin assessment