Main

The global food system has supported the accumulation of vast quantities of wealth, most notably over the past half-century through the corporatization of agriculture and fisheries1. Food systems also support the livelihoods of nearly a third of the world’s population and provide food—a basic need and human right—to all2. While global production, trade and consumption of food have escalated, these sectors have grown increasingly concentrated2 and the number of people who are food insecure continues to rise, with one in four people now food insecure3. These food system inequities are further exacerbated by contemporary global crises—such as climate change, conflict and pandemics—a pattern laid bare by COVID-19 causing near-doubling of the number of people experiencing ‘crisis level’ hunger3,4,5. Consequently, the need for transformation towards a more just and sustainable food system is undeniable3.

Social justice

Transformation towards a more just global food system requires broad-scale engagement with concepts of justice and equity. Justice broadly means ‘parity of participation’, based on the principle of equal moral worth6. Injustices are thus understood to exist where institutionalized structures create barriers that impede full participation across society6, resulting in the greatest burdens or benefits falling on particular social groups7. Injustices in food systems manifest in diverse ways; from the egregious human rights violations associated with slavery at sea8, to the negative health outcomes, such as malnutrition and maternal and child mortality, associated with a lack of food4. Struggles for justice have most often played out within territorial frames6. However, for globally connected systems, barriers to participation are increasingly constructed across national and international scales. The resulting global scope of injustice therefore necessitates global analyses6,7,9.

Analyses of injustice tend to encompass three interdependent dimensions: distributional, recognitional and representational or procedural justice6,7. Distributional injustices emerge when economic structures, such as class, mean that some people lack the resources needed to fully participate. Recognitional injustices emerge when social or cultural structures, such as gender, do not value or recognize certain identities, making it harder for them to participate as equals. Representational injustices emerge when political structures, that establish whose voice counts in decision-making, prevent some people from participating fully7. All three dimensions are relational and interact with one another to create unequal distributions of benefits (and burdens) and exacerbate conditions such that some social groups lose out, in terms of resources and power, whereas others gain.

Here, we develop a mixed-methods approach (Fig. 1) that draws on a three-dimensional justice lens6,7 and uses data from 2006 to 2016 on food system benefits and associated national policies of 194 countries, to evaluate inequalities and injustices. Such an approach, through its focus on barriers as the conditions of injustice, can also illuminate how injustices can be resolved. We focus on the highly traded10, socially valuable11,12,13, aquatic food system, which although characteristic of many food systems is only recently gaining attention.

Fig. 1: Heuristic showing the relationship between three dimensions of justice and the research framework followed.
figure 1

This diagram distinguishes between equality and justice and describes how the research questions draw on three dimensions of social justice14,15 to guide the analysis and implications for aquatic food policy.

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Results and discussion

Unequal distributions of aquatic food benefits

Focusing on three aquatic food system benefits associated with production (quantity of food produced), distribution (value of export revenues) and consumption (dietary supply of protein) of aquatic foods and using the Gini index14, we found that aquatic food system benefits were distributed highly unequally across countries (Fig. 2). Distributions in the quantity of food produced (Gini = 0.76, where 1 is perfectly unequal) (Fig. 2a) and value of export revenues (Gini = 0.90) (Fig. 2b) were more unequal than income (Gini = 0.65)15. A few high-income countries, including Iceland and Norway, produced the most per worker (253 and 171 t worker−1 yr−1, respectively) (Fig. 2a and Supplementary Data; ref. 16) despite China, India and Indonesia, where most fish workers live10,11, dominating total production (Supplementary Data; ref. 16). High-income or island nations, including Iceland, Norway and Seychelles, dominate per capita export revenue (Fig. 2b and Supplementary Data; ref. 16), whereas the quantities of aquatic foods exported are greatest in resource-rich countries, with large Economic Exclusive Zones (EEZ), such as China, Norway and Peru, which together account for 23% of global exports by volume (Supplementary Data; ref. 16). As a group, aquatic foods are among the most highly traded food commodities, in part due to the increasing commodification of fishery products and the rise of foreign processing17. Between 1994 and 2012, global seafood trade nearly doubled18, generating over US$164 billion globally in export revenues in 2018 (ref. 10). This growth in seafood trade may have exacerbated inequalities19, as globally traded aquatic foods interact with domestic markets and small-scale fisheries by diverting products to foreign markets and through competition with imported products20. However, these interactions are not universal and the impacts are context-dependent.

Fig. 2: Global distribution of benefits from aquatic foods.
figure 2

a–c, Global distribution of production (t worker−1 yr−1) (n = 144) (a), exports (US$ capita−1 yr−1) (n = 188) (b) and aquatic protein supply (g capita−1 d−1) (n = 167) (c), represented as global map with insert for Lorenz curves with Gini coefficients. Grey colour represents countries with missing data.

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Consumption of aquatic foods (as protein supply) was more equally distributed than production or export revenues but still exhibited high inequality (Gini = 0.46; Fig. 2c). Aquatic food consumption comprises around 17% of animal protein consumption globally10,16. The highest levels of consumption were found in island nations across the Atlantic, Pacific and Indian Oceans, including the Maldives, Iceland and Kiribati (47, 27, 24 g capita−1 d−1 of protein, respectively) (Supplementary Data; ref. 16). In comparison, for 100 countries (60%) consumption was below the global average of 5.5 g capita−1 d−1 of protein (Supplementary Data; ref. 16). Because there are limits to how much someone can eat, the range of consumption values is smaller than the range of values for production and trade, which partly explains the more equal distribution. However, small increases, or decreases, in consumption of aquatic foods can substantially impact nutrition. This is particularly true in low-income countries21,22 where up to 845 million people depend on aquatic foods as a critical source of essential micronutrients12,13 but where supply is at, or close to, levels needed to meet requirements for a healthy diet21. The emerging emphasis on aquatic foods as a healthy and sustainable alternative to meat could undermine this potential if aquatic foods flow increasingly towards high- and middle-income consumers and countries23.

National policies differ in awareness of barriers

To evaluate awareness of barriers to participation within national aquatic food policy, we conducted eight expert interviews to identify terms that reflect economic (for example, wealth), social (for example, gender) or political barriers (for example, voice) and policy concepts (for example, social security) that seek to address these barriers (Supplementary Table 2). We then used these terms and concepts in a summative content analysis24 conducted on 173 countries aquatic food production-related (for example, fisheries and aquaculture) and consumption-related (for example, food and nutrition security) policy documents, comprising 306 enacted laws and policies in total (Methods). We found globally that policies were most likely to recognize or seek to address economic barriers, most often related to wealth and trade (Fig. 3 and Supplementary Table 3). This policy orientation was particularly true for southern Africa (Fig. 3), a region with some of the highest levels of income inequality in the world25. Overall, policies were least likely to recognize or seek to address political barriers (Fig. 3).

Fig. 3: Recognition of barriers to participation in national policy documents.
figure 3

Average number of references made to economic, social and political barriers in enacted national policy documents (n = 306). Petal diagrams describe the average number of references per page across UN subregions. Colours: dark blue, Africa; light blue, Oceania; yellow, Europe; orange, Caribbean; green, Americas; purple, Asia. Grey colour represents countries with missing data.

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We found considerable variation in attention given to social barriers, including gender and age (Fig. 3 and Supplementary Table 3). Policies from eastern Africa and southern and western Asia, where prevalence of malnutrition is high and a particular concern for women and children4, contained the most frequent references to social barriers, in particular age (Fig. 3). In contrast, policies from eastern Europe contained the fewest (Fig. 3). References to social barriers were particularly low across production-related policies where on average fewer than 0.1 references were made, per page, compared to over ten times more (1.2) in consumption-related policy documents (Supplementary Table 3). This suggests a broad failure within production-related policies to recognize and account for differences in social identity (for example, gender and age). Fifty-three and 84 (20% and 30%) countries’ production policies made no reference to age or gender, respectively, compared to only three and nine countries’ consumption policies (Supplementary Data), highlighting the slow progress in moving beyond gender-blind production-related policies26. Yet, global prevalence of child labour remains high27 and ample evidence exists that gender norms and social constraints limit aquatic food system actors from participating equally28.

Historical and sociocultural differences in how production and consumption sectors are perceived26,29, have created little overlap between sectors in awareness of barriers, reflecting a lack of institutional coordination. Differences were particularly stark in some geographies. For example, production-related policies from Vietnam and the Democratic Republic of Congo made some of the most frequent references to economic barriers and least frequent to social barriers. Conversely, their consumption-related policies were amongst the least likely to reference economic barriers and most likely to reference social barriers. Consumption-related policies from Bangladesh and Australia similarly make some of the most frequent references to social barriers but their production-related policies make the fewest (Supplementary Data).This focus, on overcoming economic barriers in the production of aquatic foods and social barriers in the consumption of aquatic foods, rather than removing barriers to access, is likely to reinforce divisions of labour that are shaped by traditional social and cultural norms29. Greater investments in mother- and child-focused health probably account for differences between production- and consumption-related policies30. However, differences across sectors in awareness of, and efforts to address, barriers can also present an opportunity for cross-sector policy engagement to embed gender and broader socially sensitive strategies into production policies.

Barriers that create injustice

We developed a series of Bayesian models (Methods) to establish whether unequal distributions of benefits in the global aquatic food system are associated with barriers to participation, reflecting injustices. We focus on seven economic, social and political barriers to participation and eight production, distribution and consumption benefits from aquatic food systems. Because food system distributions can also result from natural variations in resource endowments9,31, in each model we control for relevant biophysical and geographic variables (for example, EEZ area and climatic zone) that are known to influence the overall size of benefits but are not relevant to our analysis of barriers.

We found that when economic barriers were lower, characterized by wealthier countries with greater levels of educational attainment, aquatic food consumption per capita and production per worker was higher (Fig. 4). Indeed, increases in fish consumption are often attributed to increases in income32. In contrast, when economic barriers are higher, characterized by lower educational attainment, we find that diets are more dependent on aquatic foods, aquatic foods are more nutritious and jobs more dependent on the aquatic food system (Fig. 4). Together, this suggests that economic barriers are associated with distributional injustices that limit wealth-based benefits but create welfare-based dependencies with livelihoods more dependent on the aquatic food system; dynamics that can lead to poverty traps33.

Fig. 4: Bayesian hierarchical models establishing how economic, social and political barriers are associated with distributions of aquatic food benefits.
figure 4

Standardized effect sizes for the influence of economic, social and political barriers on aquatic food benefits. ‘Employment (women)’ refers to women’s employment only in the direct sector. Parameter estimates are median values of Bayesian posterior distributions. Darker shaded circles indicate that 90% of credible intervals do not overlap 0 and that the estimate was either positive (blue) or negative (red). Lighter shaded circles indicate that 50% of credible intervals do not overlap with 0 and that the estimate was either positive (blue) or negative (red). White circles indicate that 50% of credible interval overlap 0. Thick and thin horizontal lines are 50% and 90% credible intervals. For all models, n = 195.

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Economic and political barriers often co-occurred to create distributional and representational injustices that reinforced a wealth–welfare divide across the aquatic food system (Fig. 4). Greater wealth-based benefits, including greater production, export and consumption of aquatic foods, were found where political barriers were lower, characterized by high levels of voice and accountability (that is, democratic processes and freedom of expression). In contrast, where political barriers, due to the lack of voice and accountability, were present, more jobs (including for women) and more affordable aquatic foods were evident (Fig. 4). Policies capable of addressing economic and political barriers to participation are desirable; however, global aquatic food system dynamics have created welfare-based dependencies that limit the potential to escape poverty33. Care is thus needed to ensure that the welfare functions, crucial to food and nutrition security, are not undermined34.

In contrast to economic and political barriers that limit wealth-based benefits, social barriers tended to limit welfare-sustaining benefits. For example, where gender-based barriers were lower (greater gender equality), aquatic foods were more affordable (Fig. 4). Indeed, gender and development research show that if women had equal access to productive assets and resources and were free from other gendered constraints, the number of food-insecure people could be reduced by up to 17% (ref. 35). Similarly, where linguistic diversity, a proxy for cultural diversity36, was higher aquatic food systems supported more jobs, although exported less (Fig. 4). Diverse cultures are more likely to reflect a diversity of practices37 that support a larger workforce, whereas homogenous cultures may have more specialized production practices that support fewer jobs but, in the current system, have greater export potential34. Many low-income countries look to exports to generate economic growth38. However, trade-induced economic growth will only benefit domestic food and nutrition security if countries can absorb the excess labour force and have policies that redistribute export revenues in a just manner, domestically34. Indeed, the tensions between welfare-sustaining (for example, local jobs and affordable nutrition) and wealth-generating (for example, revenue and profit) contributions from aquatic foods have led global food justice and food sovereignty movements to push back against the increasingly global and lucrative trade in aquatic foods, to advocate for greater support for domestic markets, household production and local domestic consumption39. National food policy therefore needs to balance support for diverse production systems that sustain jobs and are likely to be more resilient40 with export-led economic growth that risks undermining the welfare functions of aquatic food systems41.

Policy attributes for change

A positive deviance approach has been used previously in nutrition and marine research to identify and learn from places performing better than expected42. We drew on this approach to identify, for each of five benefits and given barriers present, the 12 countries securing considerably more and considerably less aquatic food benefits than expected. Selections were based on the largest standard deviations from our Bayesian models (Methods). We then qualitatively analysed the content of the resultant policies of countries to establish how barriers are addressed and consequently how national policy can better support justice in aquatic food systems. Although the content of policy documents does not always reflect practices on the ground43, it can help to create the conditions for more positive change.

Policies differed considerably in how (Table 1) and how often (Fig. 3) they engaged with social barriers. Since social barriers limit welfare-based production and consumption benefits (Fig. 4), differences in policy engagement with barriers were associated with outcomes (Table 1). For example, in Bangladesh and Gambia where aquatic food outcomes were greater than expected, nutrition policies clearly centred principles of justice and human rights, often starting with a declaration such as ‘Nutrition also is a basic human right’ (Table 1). These policies also endorsed wider responsibility for change by challenging unequal gender norms and envisioning new ones; such as promoting ‘male participation in the provision of nutritional care and support for women and their families’ (Table 1). In contrast, policies from countries with lower-than-expected aquatic food outcomes tended to interpret social barriers narrowly or in ways that risked reinforcing unequal social norms and harmful stereotypes. For example, policies that stated “[these] risks may then be compounded [...]; which will lead to another generation of malnourished mothers, who will in turn replicate the cycle” (Table 1), implicitly position women at the centre of cycles of intergenerational undernutrition and poverty and risk repeating widespread policy failures that inadvertently lay the blame44 or place the burden for change45 on women, the marginalized or poor. Policies that centre principles of justice and human rights and open up spaces to challenge norms that create constraints, without reinforcing stereotypes, can support more just food systems; strategies that are now recognized as effective levers of change28.

Table 1 Aquatic foods policy attributes and example quotes
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Redistributive approaches were frequently used to address economic barriers, that limit wealth-based benefits. For example, the fisheries policies of the Philippines, Peru and Liberia, grant small-scale fisheries and aquaculture workers preferential access to credit or exclusive access to fishing grounds (Table 1). Although economic barriers are most frequently addressed in national policies (Fig. 3), nations securing more aquatic food benefits than expected went further in their redistributive policies to make the case for justice claims, clearly outlining how structural drivers such as poverty and gender norms shape, intersect and reinforce unjust outcomes. For example, the Philippines nutrition policy acknowledged that women who were “nutritionally vulnerable [and] from poor families and communities have less access to resources and services” (Table 1). Such redistributive justice claims that clearly acknowledge the causes of injustice can avoid inadvertently promoting destructive notions such as the ‘undeserving poor’46. Political barriers, which also limit wealth-based benefits (Fig. 3), were in contrast least likely to be mentioned, particularly in consumption-related policies; however, the nutrition policy of Liberia was an exception, exemplifying downward accountability (Table 1). Other exceptions were from countries that secured more aquatic food benefits than expected, whose fishery policies outlined clear processes for inclusive decision-making that looked to support equal opportunities and build accountability (Table 1), highlighting the potential for inclusive decision-making processes to support more just food systems.

Aquatic foods are critical to health, economies and livelihoods10,12 but economic, social and political barriers mean their benefits are unevenly accessed, leading to costly unmet nutritional needs. Policies can steer food systems towards more parity in access to productive, affordable and nutritious foods. Five policy recommendations emerge from this work that can help support justice across aquatic food systems. These recommendations are not exhaustive and, because injustices are intersecting, multidimensional and cross-scale6, apply both nationally and beyond national boundaries. Overall, we found that more just aquatic food policies:

  1. (1)

    Centred principles of justice and human rights47 and challenged existing social norms28; in doing so, these policies seek to minimize social barriers and support welfare-based benefits of aquatic foods without placing the burden of change on the disadvantaged45

  2. (2)

    Provided clear guidance on inclusive decision-making processes and downward accountability to address political barriers and support more equal access to wealth-based benefits of aquatic foods

  3. (3)

    Identified and specified the structural drivers or conditions, of injustice, so that redistributive policies that address economic barriers and support more equal access to wealth-based benefits, can do so without inadvertently disempowering or ‘moralizing’, the disadvantaged46

  4. (4)

    Built strong cross-sectoral engagement between production and consumption sectors48 and supported colearning to develop policies that support more inclusive production practices and more representative consumption practices and in doing so avoid reinforcing harmful social norms

  5. (5)

    Recognized the inherent tensions between wealth-generating and welfare-sustaining benefits, appreciating that this requires coordination and concession across scale, underscoring the importance of pan-national efforts, such as the Committee on World Food Security, to inform global negotiations and agreements47

Moving towards a more just aquatic food system will require both a renewed emphasis on justice in policy formulation and increased investment by states and their development partners in supporting governance reform in the sector23,48. These actions will help to ensure that the benefits of aquatic foods are more equitably distributed and accessible to populations that need them most.

Methods

We develop a mixed-methods approach to examine aquatic foods through a three-dimensional justice lens6,7 (Fig. 1). We first use a Gini coefficient14 to quantify how (un)equally benefits are distributed (Fig. 2). Next, we combine expert interviews with a summative content analysis24 of national production and consumption-related policies49 to quantify the extent to which policies recognize economic, social and political barriers to participation (Fig. 3). Third, we develop a series of Bayesian hierarchical models50 to establish whether economic, social or political barriers are associated with the unequal patterns of distribution (Fig. 4). Finally, we combine a positive deviance (or positive outlier) approach42,51, to identify countries securing considerably more (and less) aquatic food system benefits than expected given the barriers present, with an interpretative policy content analysis24, to qualitatively analyse the content of their national production- and consumption-related policies and identify policy actions likely to support more just food system outcomes (Table 1).

Distribution of benefits using Gini coefficient

We focus on three aquatic food system benefits (quantity of food produced, value of exports and quantity of food consumed (Supplementary Methods)) and use a Gini index14 to examine how unequal the distributions of benefits are across country. For each variable we plot the Lorenz curve and calculate the unweighted Gini coefficient using the R package reldist (Fig. 2). Gini coefficients represent the area between a line of equality and a curve of the benefit distribution when plotting the cumulative share of the population versus the cumulative share of the benefit. The unweighted Gini coefficient applied to per capita estimates of benefits measures between-nation inequality in the distribution of benefits, aligning with the response variables in our subsequent Bayesian models below. We plotted values for production (t worker−1), distribution (US$ capita−1) and consumption (g capita−1 d−1) by nation to visualize patterns globally.

Policy engagement with barriers

Expert interviews

We first conducted eight guided expert interviews with academics and practitioners working in aquatic food systems to: (1) identify policy (and legal) documents; (2) identify terminology, which when used in policy documents suggests recognition of or engagement with economic, social or political barriers to participation; and (3) conceptualize policy attributes likely to be used in efforts to overcome barriers faced by different social groups in accessing benefits associated with aquatic food systems. Academics and practitioners (some of whom are co-authors) were identified through our networks to cover a range of geographies (South America, Africa, United States, Asia and Global) and areas of expertise (fisheries, aquaculture, public health, development and trade). Ethics was granted through the Lancaster University ethics board to C.C.H., approval number FST18132.

All concepts identified in the interviews that either recognized or attempted to overcome a barrier were grouped thematically into the categories of barrier they were most closely associated with (Supplementary Table 2). Economic barriers were thematically grouped as wealth, safety net policies and policies to improve market access and domestic trade. Social barriers were thematically grouped as gender, age and policies to support access to health for vulnerable populations. Political barriers were thematically grouped as human rights, access rights and participatory processes (Supplementary Table 2). Although terms capturing cultural identity were specified (for example, groups capturing differences in ethnicity, religion, caste and race), these were not included in subsequent analyses as they tended to be geographically specific, making selection of representative terms, for a global analysis, impossible.

Legal and policy documents

We next compiled 344 production- and consumption-associated policy and legal documents from 173 countries, written between 1991 and 2020 (Supplementary Methods; ref. 49). All documents were produced by national fisheries, agricultural, environmental and health agencies themselves or in conjunction with United Nations organizations including the World Health Organization and the Food and Agriculture Organization. These documents are not necessarily evidence of policies in practice but reflect prerequisite enabling conditions, recognizing that policy development and implementation take time and acknowledging that policies de jure are not necessarily de facto practices43. Furthermore, these documents are not exhaustive of all aquatic food policies but represent a comparable and nationally representative global sample of production and consumption policies to provide an indication of the levels of awareness of the challenges associated with social difference.

Summative keyword analysis

We finally, conducted a summative qualitative content analysis24 to quantify the extent to which national policies recognize barriers to participation. We scanned all consumption-related policies in NVivo 2020 for terms that relate to aquatic foods (for example, fish and fisheries) (Supplementary Table 2). Consumption policies that made no reference to aquatic food terms were removed from subsequent analysis. We autocoded the remaining 306 production and consumption policy documents in NVivo 2020 for terms (Supplementary Table 2) capturing economic, social and political barriers identified through the expert interview. Analyses were conducted in five languages, covering 98% of all countries. For each policy, the number of references to each keyword was extracted and divided by the number of pages in the policy. For each theme (that is, wealth, safety nets, access to markets, age, gender, health- and nutrition-sensitive policies, human rights, access rights and representation), references per page were calculated by summing across all keyword references within a theme (for example, woman + maternal = gender) and averaging across policy type (consumption and production) (Supplementary Table 3). The summarized keyword theme references per page were then merged with global shape files in the sf R package52 (Fig. 3; Supplementary Fig. 5).

Associations between barriers and benefits

We draw on social justice theory, based on the principle of ‘equal moral worth’6, to evaluate whether economic, social and political barriers to participation are associated with the unequal distributions of aquatic food systems benefits (Fig. 2). To do so, we developed a series of Bayesian hierarchical models to establish whether seven indicators of economic (wealth and education), social (gender inequality, linguistic diversity, cultural hegemony and age) and political (voice and accountability) barriers, explain patterns of distribution for eight benefits—production (quantity, quality, employment and women’s employment), distribution (export revenues and affordability) and consumption (quantity and reliance) (Fig. 4)—while controlling for environmental, geographical and economic factors, that do not constitute barriers to participation but are likely to influence the benefit of interest (Supplementary Methods, Supplementary Figs. 1 and 2 and Supplementary Table 1).

Although differences exist in how the production, distribution and consumption of aquatic foods have evolved across different countries associated with history, religion and culture that influence current production, distribution and consumption, these are beyond the scope of this study. Our analyses are therefore limited to an evaluation of current practices and not to disentangling historical patterns of evolution or their role in driving policy changes.

Bayesian hierarchical model development

Before model development and for each of the eight aquatic food system benefits, we built a series of expert-informed directed acyclic graphs (DAGs)53 (Supplementary Fig. 2) to explore interactions between our dependent, independent and control variables. The purpose of using DAGs in this exercise is to identify otherwise invisible confounding, particularly collider, bias where two variables simultaneously act on a third and induce correlation among them53,54,55. Where colliders were found, they were removed to avoid inducing collider bias (see Pearl’s DAG-based approach53) and remaining variables were checked for correlations between variables (Supplementary Fig. 3). This DAG-based approach was developed to be more transparent about the underlying assumptions than including nuisance variables without checking for the range of confounding issues that they can induce. Because of the transparency of this approach, DAGS are often used for causal analyses; however, we do not use formal causal inference in this study.

Our final DAGs, after removing colliders and highly correlated variables included 9 environmental, geographic and economic control variables (EEZ area, primary productivity, maximum inland water, climatic zone, capture production, aquaculture production, imports, exports and affordability) across 8 models (production, employment, women’s employment, nutrient density, exports, affordability, consumption and reliance) (Supplementary Figs. 1 and 2).

Aquatic food production is likely to be affected by natural productivity and the water available to produce aquatic foods. We therefore included EEZ area (km2), primary productivity (mg C m−2d−2) and maximum inundation area (1,000 km2) in the model for production per worker. The nutrient quality of aquatic foods is likely to be influenced by climatic zones2, we therefore included climatic zones1 in the model for nutrient quality. Employment, export revenues and affordability are likely to be affected by the size of the sector, we therefore included total capture production (t) and total aquaculture production (t) as the sum of marine, freshwater and brackish aquaculture production (t) in the models for total employment, women’s employment, export revenues and affordability. Affordability of aquatic foods is in addition likely to be influenced by unit value of imports and exports. We therefore added unit export revenues (exports in US$1,000 divided by exports in tonnage) and unit import costs (imports in US$1,000 divided by imports in tonnage) to the model for aquatic food affordability. Consumption and reliance of aquatic foods are likely to be influenced by the relative affordability of aquatic foods, we therefore added fish relative caloric price (affordability) into the models for consumption of, and reliance on, aquatic foods.

After we identified and selected our 8 dependent, 7 independent and 11 control variables (maximum of 4 for any given model) on the basis of the descriptions above and before the analysis, we first log-transformed highly skewed independent and control variables (wealth, EEZ area, maximum inundation area, capture production, aquaculture production, unit exports and unit imports). Then, we standardized all independent and control variables by centring at the mean with a unit standard deviation. Finally, we scaled all dependent variables by dividing by an interquartile range and multiplying by 100, so that we could use the same parameterization for prior distributions across all models.

All hierarchical models were specified with three levels: global, regional and national. For regions, we extended subregions defined by the United Nations into 22 finer regions (Australia and New Zealand, Polynesia, Northern Africa, Western Europe, Middle Africa, Southern America, Northern America, Eastern Africa, Southern Europe, Southeastern Asia, Eastern Asia, Northern Europe, Central America, Southern Asia, Western Africa, Eastern Europe, Caribbean, Melanesia, Micronesia, Central Asia, Southern Africa and Western Asia) to take into account cultural differences. In region i, intercept β0i was drawn from a normal distribution (equation (1)) and standard deviation σi was drawn from a gamma distribution (equation (2)) as:

$$\beta _{0i}\sim {{{\mathrm{Normal}}}}\,{{{\mathrm{(}}}}\mu {{{\mathrm{ = }}}}\mu _0{{{\mathrm{,}}}}\,\sigma {{{\mathrm{ = }}}}\sigma _{{{\mathrm{0}}}}{{{\mathrm{)}}}}$$
(1)
$$\sigma _i\sim {{{\mathrm{Gamma}}}}\,{{{\mathrm{(}}}}\alpha {{{\mathrm{ = }}}}\alpha _0{{{\mathrm{,}}}}\,\beta {{{\mathrm{ = }}}}\beta _{{{\mathrm{0}}}}{{{\mathrm{)}}}}{{{\mathrm{.}}}}$$
(2)

In nation j, intercept β0ij was drawn from a normal distribution (equation (3)) with a regional mean and standard deviation as:

$$\beta _{0ij}\sim {{{\mathrm{Normal}}}}\,{{{\mathrm{(}}}}\mu {{{\mathrm{ = }}}}\beta _{0i}{{{\mathrm{,}}}}\,\sigma {{{\mathrm{ = }}}}\sigma _{{{\mathrm{i}}}}{{{\mathrm{)}}}}{{{\mathrm{.}}}}$$
(3)

These intercepts were passed into a linear model (equation (4)):

$$\mu _{ij} = \beta _{0ij} + {\mathbf{\upbeta}} {{\mathbf{X}}},$$
(4)

where β is a vector of coefficients and X is a design matrix with independents. Finally, the logarithm of the observed value yij was modelled using a t-distribution, with μ = μij, σ = σerror and v = 5. The data likelihood was chosen by checking leave-one-out probability integral transform (LOO-PIT)55. LOO-PIT diagnoses whether future unobserved data will follow the same distribution of the observed data by applying probability integral transform to leave-one-out cross-validation and estimating a cumulative density distribution of the posterior predictive. Our results show uniform distributions (Supplementary Fig. 4; also see Code availability), indicating proper model specifications. Global parameters were specified using weakly informative priors, with a normal distribution with μ = 0 and σ = 100 for μ0 and with a half-Cauchy distribution with β = 5 for α0, β0, σ0 and σerror. Missing independent and control variables were imputed from a covariance matrix with LKJ Cholesky covariance priors. For LKJ Cholesky distribution, we used η = 2 and standard deviation specified as an exponential distribution with λ = 1. Log-transformed population was also included in the matrix, as it was correlated with some of the independent variables. For each model, the parameters were sampled using the NUTS algorithm over two chains with 5,000 sampling each in PyMC3 v.3.10.0 (ref. 55) under Python v.3.8.0. Model convergence was supported by Gelman–Rubin statistics (\(\hat R\)) all close to 1 (ref. 56).

Attributes associated with more just outcomes

Positive deviance approach

Focusing on production, employment, affordability, consumption and reliance as the outcomes most likely to be influenced by production- and consumption-related policies, we identified, for each, 12 outliers defined as the nations with the greatest (positive and negative) standard deviations. Positive outliers thus represent areas with better-than-expected aquatic food outcomes (for example, aquatic food is considerably more affordable than expected) given the barriers present and negative outliers are places with worse-than-expected outcomes (for example, aquatic food is considerably less affordable than expected). We used outputs from the Bayesian models on the standard deviation of each nation’s intercept from the expected regional distribution (equation (2)). For each benefit, six ‘positive’ and six ‘negative’ outlier countries were identified (Supplementary Table 4).

Interpretative qualitative policy content analysis

We then qualitatively analysed, in depth, the content of five randomly selected positive outlier country policies (Bangladesh, Gambia, Liberia, Peru and the Philippines) and three randomly selected negative outlier country policies (Ethiopia, Finland and Sudan) to understand how countries experiencing fewer injustices use terms that capture economic, social and political barriers in policy. We looked for evidence, depth and sophistication of engagement with distributional, representational and recognitional dimensions of justice and further coded for emergent themes demonstrating engagement across dimensions of justice and across sectors relevant to aquatic foods. Drawing on our guided interviews and iterative readings, we identified ten themes: three representing inadvertently damaging language, likely to translate to policy failings; and seven representing progressive language and context, likely to translate into policies capable of overcoming economic, social and political barriers (Table 1).

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.