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Reducing waste in nutritional epidemiology: review and perspectives

Published online by Cambridge University Press:  19 February 2019

Dana Hawwash
Affiliation:
Department of Food Technology, Safety and Health, Ghent University, Ghent, Belgium
Chen Yang
Affiliation:
Department of Food Technology, Safety and Health, Ghent University, Ghent, Belgium
Carl Lachat*
Affiliation:
Department of Food Technology, Safety and Health, Ghent University, Ghent, Belgium
*
*Corresponding author: Carl Lachat, email [email protected]
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Abstract

We discuss efforts in improving the value of nutrition research. We organised the paper in five research stages: Stage 1: research priority setting; Stage 2: research design, conduct and analysis; Stage 3: research regulation and management; Stage 4: research accessibility and Stage 5: research reporting and publishing. Along the stages of the research cycle, varied initiatives exist to improve the quality and added value of nutrition research. However, efforts are focused on single stages of the research cycle without vision of the research system as a whole. Although research on nutrition research has been limited, it has potential to improve the quality of nutrition research and develop new tools and instruments for this purpose. A comprehensive assessment of the magnitude of research waste in nutrition and consensus on priority actions is needed. The nutrition research community at large needs to have open discussions on the usefulness of these tools and lead suitable efforts to enhance nutrition research across the stages of the research cycle. Capacity building is essential and considerations of nutrition research quality are vital to be integrated in training efforts of nutrition researchers.

Type
Conference on ‘Multi-stakeholder nutrition actions in Africa: Translating evidence into policies, and programmes for impact’
Copyright
Copyright © The Authors 2019 

Poor diets are a risk factor for global health and mortality. In 2016, the United Nations General Assembly declared a Decade of Action on Nutrition, which provides an unprecedented momentum to drive concerted action and improve diets and malnutrition in all its forms(Reference Baker, Hawkes and Wingrove1). Nutrition research plays a pivotal role in this process as it provides evidence-based recommendations to guide interventions, policy, practice and rational allocation of resources towards achieving the best possible health outcomes.

However, understanding what constitutes an optimal diet, remains a challenge(Reference Mozaffarian, Rosenberg and Uauy2). The human diet presents a complex exposure for health with many interacting components(Reference Satija, Yu and Willett3). Furthermore, nutritional epidemiological research relies on different types of study designs including experimental and observational designs, each with important limitations. Well-designed studies powered to assess long-term health outcomes are rare(Reference Ioannidis4).

Substantial concerns regarding the quality and credibility of nutritional epidemiological research findings have recently emerged(Reference Archer, Pavela and Lavie5, Reference Ioannidis6). The nutrition science is fraught with concerns about private sector influences in agenda setting, design, implementation of studies and presentation of research findings for commercial interest(Reference Nestle7). Scholars have challenged the conceptual basis and proposed a major overhaul to ensure societal value, credibility and conceptual relevance in the years to come(Reference Penders, Wolters and Feskens8).

In 2014, an assessment of biomedical research described ‘research waste’ as any research that ignores the needs of any possible user (including patients, practitioners and policy makers) of the research output, as well as research that is conducted in isolation of current evidence (concurrent research and past)(Reference Chalmers, Bracken and Djulbegovic9). The series scrutinised underlying issues in biomedical research that lead to waste, including poor consideration of existing knowledge and priority of stakeholders, poorly designed and managed research, unethical conduct of research and incomplete or inaccessible research output(Reference Chalmers, Bracken and Djulbegovic9Reference Glasziou, Altman and Bossuyt13).

The current paper reviews progress to address waste in nutrition research to date.

In doing so, it aims to define knowledge gaps and inform wider considerations about the quality of nutrition research. The review is organised according to the research cycle as proposed earlier by Chalmers et al.(Reference Chalmers and Glasziou14) from priority setting to dissemination of research results. After summarising the challenges per research stage, we provide examples of relevant on-going initiatives in nutrition. Table 1 is a concise summary of efforts in nutrition research per research stage.

Table 1. Developed tools to improve the quality of nutritional epidemiological research

Stage one: research priority setting

Waste in research can be traced to the earliest stage in the cycle, when priorities on what to study are being set. For research to be relevant, it needs to address the interests of patients, consumers and the wider public. Priority setting is key to ensure research addresses the needs of stakeholders and adds societal value(Reference Chalmers, Bracken and Djulbegovic9). Amongst others, careful consideration of investment by funders, inclusion of stakeholders and consideration of prior existing knowledge are needed to justify new research efforts.

However, given the wide interest and isolated actors in nutritional epidemiological research, agenda setting is not a panacea(Reference Morris, Cogill and Uauy31). Tools for priority setting exercises have been developed such as the Delphi rounds and the Child Health and Nutrition Research Initiative(Reference Rudan, Gibson and Ameratunga32) and provide a structured approach to define priorities in nutrition research using online consultation rounds.

There are ample initiatives that have documented priorities for nutrition research or proposed a formal nutrition research agenda. A recent scoping review identified twenty-seven reported nutrition research priority setting exercises in 2018(Reference Hawwash, Pinxten and Aubert Bonn18). As an example, Haddad et al. proposed a global nutrition research agenda that focuses on creating food systems that foster nutrition rather than feeding populations within the context of Sustainable Development Goals(Reference Haddad, Hawkes and Webb33).

Concerns have emerged about the transparency and ethics during the priority setting process, in particular related to food industry efforts to influence agenda setting in nutrition research. The processes through which private corporate funding have affected research focus have meanwhile been well described and understood(Reference Serodio, McKee and Stuckler34). For example to direct research efforts towards energy balance and exercise, instead of the effects of sugar(Reference Fabbri, Chartres and Scrinis35).

Much less focus has been given to transparency and accountability of non-private sector stakeholders that are involved in nutrition research. There is an apparent need for stakeholders, such as funders and researchers to be transparent to ensure accountability and monitoring of commitments. Most of the research priority setting efforts are led by researchers in high-income countries(Reference Hawwash, Pinxten and Aubert Bonn18). Specific efforts are required to forge equitable relationships with researchers in low- and middle-income countries when setting nutrition research priorities. A review of nutrition research in Africa for instance indicated how research agendas are largely driven by donors or academia in high-income countries(Reference Lachat, Nago and Roberfroid36). In addition, African researchers perceive research findings to be poorly considered by local policy makers and integrated in action(Reference Van Royen, Lachat and Holdsworth37). Although a partnership was established to support an African-led and evidence-driven research agenda in Africa, the initiative was underfunded and short-lived(Reference Aryeetey, Holdsworth and Taljaard15).

Moreover, values that underpin decisions for specific priorities are poorly reported in nutrition priority setting efforts. In accordance with the development of the Research Fairness Initiative to foster fair and responsible actions within global joint research and advances in health(38), a tool was developed to ensure transparency and consideration of values when setting research priorities in nutrition(Reference Hawwash, Pinxten and Aubert Bonn18), which is required to be tested and monitored in the years to come.

Investment in new research should consider the extent to which this research adds value to the existing knowledge. To ensure added value of new studies, knowledge gaps need to be considered, preferably through a systematic review and quality appraisal of evidence(Reference Chalmers, Bracken and Djulbegovic9). Systematic and mapping reviews are increasingly being used in nutrition research(Reference Balk, Horsley and Newberry39). Yet, most systematic reviews have focused on nutrition specific interventions and supplements and curative approaches. The available methods to assess evidence in medicine might not be readily applicable to wider dietary and food system interventions(Reference Lawrence, Naude and Armstrong40). The multi-sectoral nature of nutrition research presents particular challenges to identify and retrieve relevant papers. To address this, a specific search syntax (or hedge) to retrieve food, diet and nutrition related manuscripts from PubMed is proposed(Reference Rumsey19). In addition, Cochrane Nutrition was established in 2016 to summarise evidence in nutrition research(16). It presents a collaborative effort for evidence synthesis in nutrition and seeks to develop specific tools and summarise knowledge.

Grading of Recommendations Assessment, Development and Evaluation (GRADE)(Reference Guyatt, Oxman and Vist41) guidelines, which is a tool to grade the quality of evidence and recommendations in healthcare, are relevant but present challenges for nutrition research. Recently NutriGrade(Reference Schwingshackl, Knuppel and Schwedhelm17) has been proposed as a scoring system to grade the evidence of randomised controlled trial and cohort study nutrition-related meta-analysis. NutriGrade pays specific attention to certain methodological issues related to nutrition research when assessing the meta-evidence of diet-disease relations, i.e. dietary assessment methods, calibration of FFQ, the assessment of diet-associated biomarkers, the limitation of blinding participants and personnel in nutrition research.

Stage two: research design, conduct and analysis

Careful study design, conduct and analysis are cornerstones for sound research. Bias in amendable flaws at this stage, can induce implausible effects. Other issues during the implementation of research include arbitrary choice of methods, analyses and an overemphasis on reporting random extremes(Reference Ioannidis, Greenland and Hlatky12).

Available methods to assess dietary exposure have inherent limitations. Food consumption and nutrient intake vary from day-to-day, between and within populations and over the different life cycle stages(Reference Cade, Warthon-Medina and Albar42). Establishing recommended intake and nutrient requirements is equally challenging and large variations prevail between countries(Reference Pijls, Ashwell and Lambert43). Most dietary assessment tools rely on memory of the study participants and are hence subject to substantial bias and error(Reference Satija, Yu and Willett3). Furthermore, validated tools need to be carefully considered when assessing diet between specific populations i.e. minority ethnic groups(Reference Almiron-Roig, Aitken and Galloway44).

The Nutritools website(20) hosts numerous existing dietary assessment instruments and tools regarding the strengths and limitations of dietary tools(Reference Cade, Warthon-Medina and Albar42). The website has a built-in e-library that contains validated assessment tools and facilitates re-use of previous efforts. The best practice guidelines on the websites provide important guidance on crucial prerequisites for study designs, including careful consideration of the objectives and outcomes to be measured. With regard to validation studies for dietary assessment, Serra-Majem et al. have previously provided recommendations for dietary validation studies(Reference Serra-Majem, Andersen and Henrique-Sanchez45).

Spin i.e. modifications in reported findings that affect and mislead interpretation are unfortunately not uncommon in nutrition research(Reference Chiu, Grundy and Bero46). Thus, careful consideration of the methodological limitations, cost and participant burden, as well as defining and pre-registering of outcomes and exposures are required when establishing nutrition and health associations. Kirkpatrick et al. provide an overview of methodological challenges to define dietary outcomes of intervention studies, including application of biomarkers(Reference Kirkpatrick, Collins and Keogh47). The Core Outcome Measures in Effectiveness Trials fosters the development of outcomes for trials(Reference Williamson, Altman and Bagley48). To date (November 12, 2018) however, the database contains just a handful of outcomes for diet and nutrition, i.e. on the prevention of obesity and assessment of iron deficiency.

Stage three: research regulation and management

Research regulation and management entails careful consideration regarding the following: the adherence to the choice of an appropriate study design, the rigorous approaches to recruitment and retention of participants, data collection and monitoring, participants’ engagement and conflict of interest(Reference Al-Shahi, Salman, Beller and Kagan10).

Complexity in nutrition research is not limited to the measurement tools and outcome measures. Nutrition research cannot be isolated from its context, i.e. political, religious, cultural, product marketing connotation and laws. Therefore, appropriate regulation and management of nutrition research, should consider this context and any conflicts of interest(Reference Rucker and Rucker49).

To assess prevailing rules and context, a few resources are available. For instance, the WHO e-Library of Evidence for Nutrition Actions (eLENA)(21) and the WHO Global database on the Implementation of Nutrition Action (GINA)(22) provide recommendations, policies and legislations on national, regional and international levels. For instance, legislation on food fortification and breast-feeding substitutes in GINA, together with an overview of current evidence on the eLENA platform, provide context and guidance for new research regarding the promotion of appropriate breast-feeding and regulation of breast-milk substitutes.

The World Cancer Research Fund International has recently developed the NOURISHING policy framework, to encourage actions within three essential domains: the food environment (NOURIS), food system (H) and behavioural change communication (ING)(23). The framework is built to support action and research that focus on unhealthy eating.

When it comes to research management and regulation during the data collection, handling and analysis phase, there are specific training guides, procedures manuals and standard operation procedures to harmonise procedures and increase transparency. In clinical studies, institutional review boards request monitoring of data collection and reporting of safety issues(Reference Weaver and Miller50).

Appropriate declaration of conflicts of interest (e.g. financial(Reference Tseng, Barnoya and Kruger51) or dietary(Reference Schwab52, Reference Bero and Grundy53)) is a clear issue in nutrition research and further guidance on how to disclose competing interests is apparent. The WHO has developed a decision-making process as part of an approach for the prevention and management of conflicts of interest in the policy development and implementation of nutrition programmes at the country level(24).

The need to protect participants involved in nutritional research and to understand the rules concerning the use of data collected during studies has been looked at within the European Nutritional Phenotype Assessment and Data Sharing Initiative project. A set of policies has been centralised for data protection, sharing and re-use as well as ethics and intellectual property according to the legal and ethical aspect of EU countries(54).

Stage four: addressing inaccessible research

Inaccessibility of research findings can lead to redundant, misguided or potentially harmful decisions. Inaccessibility has different dimensions including language barriers, manuscripts locked behind journals pay walls, inaccessible study data, published in local, non-indexed, journals or grey literature making it irretrievable(Reference Aryeetey, Holdsworth and Taljaard15).

Similar to other types of biomedical research, open access publishing has gained popularity in nutrition. Within the Nutrition and Dietetics subject category of the Web of Science for instance, eleven of the eighty-three journals publish only open access papers. Most other journals provide options to publish manuscripts under an open access license. Popular repositories for trials such as Clinical Trials(55), WHO's International Clinical Trials Registry Platform(56) or systematic reviews such as PROSPERO(57) include nutrition-related studies.

Capitalising on the existing research data is a promising way to add value to research e.g. through meta-analysis, re-analysis or pooling of data to increase power of (subgroup) analysis. The Global Burden of Disease study(58), Non-Communicable Disease Risk Factor Collaboration(59) and the Global Dietary Database(60), are a few examples that demonstrate how the re-analysis of the existing data can generate new insights into diet, nutrition and human health.

Specific initiatives have emerged to consolidate and share data in diet and nutrition. The FAO/WHO Global Individual Food consumption data Tool (GIFT)(25) integrates large and small-scale surveys from countries worldwide and provides a unified database to share the existing food consumption data. Apart from merging food intake data, GIFT shares individual level data where allowed by the data provider. National Information Platforms for Nutrition, piloted in Bangladesh, Ethiopia, Kenya, Laos, Niger and Uganda, are created to collect the existing data and leverage knowledge for nutrition interventions and policies(61). Other options to share both meta and individual study level data, including intervention and mechanistic studies, are provided through the DASH-IN database(62). This database contains study data with a harmonised set of data descriptors.

In addition to more centralised approaches for data sharing, BioSHaRE-EU developed additional applications to share and access epidemiological data in a federated configuration. In this regard, DATASHIELD provides useful tools to analyse data stored at different locations within ethical and privacy boundaries that apply to the re-use of human data(Reference Gaye, Marcon and Isaeva63).

However, sharing data with several initiatives involves substantial preparations to fit the desired data requirements and templates. Given the variety of developed initiatives, streamlining data preparation would be helpful, in particular the development of a uniform standard for food intake (meta) data.

Standardised approaches to collect, analyse and harmonise dietary intake data are available from the European Food Standard Agency (EFSA)(64). FoodEx2 provides a vocabulary for disambiguation and correct description of food and its properties(64). An EFSA data transmission schema has been made available which provides a template to standardise food intake data collected using the EFSA recommendations. However, to identify studies and research data effectively, meta-data should also be accessible, preferably in a harmonised manner to facilitate searches. Many efforts have been made to establish a common set of (meta) data descriptive and facilitate identification, re-use and interpretation. Essential study descriptors were developed earlier that assist researchers to define key study characteristics(Reference Pinart, Nimptsch and Bouwman65). In addition, data quality descriptors for nutritional epidemiological research have been recently developed as metadata of nutrition and will support researchers when using the existing data for pooled or secondary analyses(Reference Yang, Pinart and Kolsteren26).

Nonetheless, leveraging the power of information science to nutrition research will require further development and applications of ontologies. Ontology is a representation of knowledge networks arranged in a taxonomic hierarchy, where a machine-readable identifier is set for each term in the knowledge network(Reference Noy and McGuinness66). Use of ontologies enables linking and processing of heterogeneous data(Reference Ashburner, Ball and Blake67). Although some progress has been made to represent the systematic classification of diet, food and nutrients(Reference Vitali, Lombardo and Rivero27) further efforts are needed to link diet and foods with the corresponding nutritional values.

Stage five: research reporting and publishing

Consequences of incomplete studies or misreporting include reaching erroneous conclusions, failure to include evidence in systematic reviews and inappropriate implementation of interventions(Reference Glasziou, Altman and Bossuyt13). Specific incentives, capacity building efforts and applications are needed to ensure research reports contain all necessary detail for readers to understand what was done and found(Reference Moher, Glasziou and Chalmers68). Reporting guidelines such as Consolidated Standards Of Reporting Trials for randomised controlled trials (CONSORT)(Reference Schulz, Altman and Moher69), Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)(Reference Moher, Liberati and Tetzlaff70) and Strengthening the Reporting of Observational Studies in Epidemiology for observational studies (STROBE)(Reference von Elm, Altman and Egger71) have been developed as authoritative recommendations to increase reporting completeness. Reporting guidelines are typically applied during the write-up of manuscripts and provide useful tools for editors and reviewers during the peer review process. The Equator Network centralises reporting guidelines(72).

Different systematic reviews have indicated how reporting completeness is also an issue in nutrition research(Reference Bekkering, Harris and Thomas73Reference Gibson, Kirk and Lecheminant75). As a response, Strengthening the Reporting of Observational studies in Epidemiology-Nutritional Epidemiology (STROBE-nut)(Reference Lachat, Hawwash and Ocke29) was developed for use in nutritional epidemiology and dietary assessment. STROBE-nut aims to incorporate previous guidelines for nutrition research and dietary assessment(Reference Burrows, Golley and Khambalia74, Reference Faber, Wenhold and Macintyre76Reference Welch, Antoine and Bertam78). The STROBE-nut checklist comprises a set of twenty-four items, organised as a checklist. An explanation and elaboration document was developed and describes good practices with examples(Reference Hornell, Berg and Forsum79). To date, most nutrition journals recommend the use of reporting guidelines and those of the BMC Springer Nature group, refer to STROBE-nut in their instructions for authors(Reference Jago and Wood80).

In addition to completeness of reporting, clear communication of research findings to non-researchers is essential. Cainzos-Achirica et al.(Reference Cainzos-Achirica, Bilal and Al Rifai81) have reviewed communication issues and related challenges for nutrition research. Specific recommendations for diverse stakeholders such as authors, journals, press and the general audience are provided. Critical communication of research findings and acknowledgement of limitations is essential, as popular misbeliefs are prevalent(Reference Brown, Ioannidis and Cope82). Unscientific beliefs about nutrition are widely present and more needs to be done to address these in order to restore trust in nutrition science(Reference Brown, Ioannidis and Cope82).

Moving forward and perspectives

The present paper summarises past and on-going efforts to improve the quality and added value of nutrition research. To our knowledge, this is the first attempt to address efforts across the entire research cycle. Several priorities emerged from the present review.

First, despite some useful initiatives, the magnitude of research waste in nutrition has not yet been assessed. Establishing a clear and integrated vision on how to address challenges in nutrition research is required first. Similar to the Lancet series on research waste(Reference Chalmers, Bracken and Djulbegovic9), a review to quantify the magnitude and prevalence of practices that lead to waste in nutrition research would be useful to guide further action. Meta research or ‘research on research’ has attracted considerable interest in biomedical sciences(Reference Ioannidis83). Although research on nutrition research has been limited, it has the potential to provide useful insights to guide interventions and develop new tools and instruments.

Secondly, reflection on what can be done, and what tools can be used at each stage for different research designs is key. Although several initiatives that can enhance added value of nutrition research have been undertaken, they are focused at single stages of the research cycle without a comprehensive vision on the research system. To address research waste, the intricate linkages between the stages of the research cycle defined earlier, should be acknowledged (Fig. 1). For example, efforts to increase data quality and accessibility cannot be seen separately from reporting guidelines of manuscripts or considerations about study designs and dietary assessment methods.

Fig. 1. Integrated view of tackling waste in nutritional epidemiological research.

Thirdly, the research community at large would eventually need to have open discussions regarding how to implement these tools, and the added value of their implementation. These discussions could drive the intention of further use and govern efforts to enhance nutrition research. The nutrition societies and in particular the International Union of Nutrition Societies would be well placed to drive this process, to establish consensus and coordinate action. Given the vast needs, prioritisation of efforts and agreement on what should be tackled first would be a useful first step. Events organised by the International Congress of Nutrition or national nutrition societies could serve as fora for dissemination and consensus building across the research community.

Fourthly, the activities listed to tackle research waste essentially address the research community. Although this is a useful start, stakeholders such as research funders, journalists, consumer societies, policymakers and publishers ideally need to be involved in this process from the onset. Involving these stakeholders would hopefully set realistic expectations for nutrition research findings. It could potentially improve important drivers of research practices such as resource allocation, and reward systems of staff and students. While we acknowledge that the whole reward system is institutionalised and internationally fixed, which can hinder potential change; the mere recognition of sound and reproducible research instead of quantity of publications and journal impact factor would be a valuable step forward.

Sound knowledge as well as a critical attitude towards dietary assessment methods and nutrition study designs are needed to foster credible findings. Specific training efforts can support the development of essential competencies for nutrition action in different professions, i.e. nutritionist, dietitians, medical doctors, food safety and technology experts, etc. To date however, it remains unclear to what extent training in research integrity and waste is incorporated and discussed in training programmes and curricula in nutrition. Additional efforts will be required to integrate critical reflection about quality and limitations of nutrition research in curricula at BSc, MSc and PhD level. In service training or online guidance would be useful for other professionals dealing with nutrition research such as journalists, dietitians and medical doctors.

In 2011, the World Public Health Nutrition Association for Public Health Nutrition has developed the competency standards of workforce(Reference Hughes, Shrimpton and Recine84), which contains considerations about the use and appraisal of nutrition research findings. This framework deserves renewed attention and enforcement within the context of the Sustainable Development Goals and the Decade of Action on Nutrition. Geographic areas with the highest burden are unfortunately those with the weakest capacity (i.e. institutional capability and geographic coverage of workforce) to act(85). Progress about curricula, capacity development and competency standards however, has been overall limited(Reference Fanzo, Graziose and Kraemer86).

Although several countries including African countries have developed nutrition-training programmes worldwide, it remains unclear which competencies are taken up and where gaps remain. A review of how current nutrition training programmes contain considerations about ethics and research integrity would be useful to guide further action. In addition, a consultative process is needed to guide discussion on the required competencies for nutrition professionals with regard to the conduct and interpretation of nutrition research findings.

Discussions on how to add value to nutrition research are timely with regard to the renewed commitment by the African Union Commission to end hunger by 2025(87) and the commitment of various African countries to scale up nutrition action(88). Well-targeted programmes to improve nutrition demand context-specific and high-quality evidence. Against a backdrop of increasing research output of nutrition research, the growing African nutrition research community would be well placed to develop an African nutrition research agenda and define priorities for cost-effective research and interventions in the decades to come.

Furthermore, and in line with the recommendations proposed by Al-Shahi Salman et al.(Reference Al-Shahi, Salman, Beller and Kagan10) research is still needed to look into, participants’ protection when nutritional epidemiological studies are conducted and consumers’ ability of understanding the provided scientific evidence, and engaging in the transition of science into public policy.

Overall, monitoring activities on the effectiveness of approaches will be needed, and collecting more feedback from researchers is key to understand how useful these tools are. It is not unimaginable that efforts to improve quality of nutrition research will result in an additional burden for researchers potentially affecting those already engaged with good research practices, and possibly leaving the problem unsolved. Care should be taken to minimise the burden on the user. A good example in this regard is the additional efforts imposed on authors to fill in reporting guidelines(89). The potential of applying new technology to increase the efficiency of a search and the quality of the output is substantial(Reference Chalmers, Bracken and Djulbegovic9). Ultimately, long-term success and adherence to the use of reporting guidelines and tools for better research will depend on how well they are integrated into the digital ecosystem of software and day-to-day practices of researchers(89). For example, ontologies for nutrition could be used to connect data collection and sharing tools. Efforts related to fair data sharing need to be incorporated at multiple stages of the cycle to increase efficiency of information sharing, retrieval and integration. Links with other ontologies such as the Cochrane PICO ontology(90) need to be fostered for this purpose.

The present review relied on published work only. We were unable to collect potentially interesting experiences from research groups and institutions that promote integrity and good research practices. Sharing those lessons learned and documenting good practices would be a useful step forward. This review did not attempt to be exhaustive and we cannot rule out missing some initiatives or manuscripts. In addition, the present review mainly considered nutritional epidemiological research. Although there are potentially similar issues in clinical nutrition and more food science-oriented research, the present focus aims to present a timely contribution to the discussion and criticisms about nutritional epidemiology.

We consider the comprehensive approach proposed in this review a useful first attempt to map existing efforts. Within the next months, we will establish a portal on initiatives to add value to nutrition research. A specific website (www.betternutritionresearch.ugent.be) will be created for this purpose and act as a portal for researchers and other stakeholders of nutrition research looking for instruments to improve quality for nutrition research and a resource for educational purposes. We welcome contributions, new efforts and other additions to complete our assessment.

Acknowledgements

The authors thank Giles Hanley-Cook and Patrick Kolsteren for the critical revision of this paper.

Financial Support

D. H. is supported by the special research fund (BOF) from Ghent University. C. L. has received funding from the FWO Research Foundation; Flanders, grant number G0D4815N. C. Y. is funded by a scholarship from the Chinese Scholarship Council. C. L. received funding from Bioversity Int. for the work on standards for dietary assessment. There was no other outside funding for this study.

Conflict of Interest

The authors have led work for nutritional epidemiology cited in this manuscript.

Authorship

The authors had joint responsibility for all aspects of preparation of this paper.

References

1.Baker, P, Hawkes, C, Wingrove, K et al. (2018) What drives political commitment for nutrition? A review and framework synthesis to inform the United Nations Decade of Action on Nutrition. BMJ Glob Health 3, e000485.Google Scholar
2.Mozaffarian, D, Rosenberg, I & Uauy, R (2018) History of modern nutrition science-implications for current research, dietary guidelines, and food policy. BMJ 361, k2392.Google Scholar
3.Satija, A, Yu, E & Willett, WC (2015) Understanding nutritional epidemiology and its role in policy. Adv Nutr 6, 518.Google Scholar
4.Ioannidis, JP (2013) Implausible results in human nutrition research. BMJ 347, f6698.Google Scholar
5.Archer, E, Pavela, G & Lavie, CJ (2015) The inadmissibility of what we eat in America and NHANES dietary data in nutrition and obesity research and the scientific formulation of national dietary guidelines. Mayo Clin Proc 90, 911926.Google Scholar
6.Ioannidis, JPA (2018) The challenge of reforming nutritional epidemiologic research. JAMA 320, 969970.Google Scholar
7.Nestle, M (2016) Food industry funding of nutrition research the relevance of history for current debates. JAMA Intern Med 176, 16851686.Google Scholar
8.Penders, B, Wolters, A, Feskens, EF et al. (2017) Capable and credible? Challenging nutrition science. Eur J Nutr 56, 20092012.Google Scholar
9.Chalmers, I, Bracken, MB, Djulbegovic, B et al. (2014) How to increase value and reduce waste when research priorities are set. Lancet 383, 156165.Google Scholar
10.Al-Shahi, Salman, R, Beller, E, Kagan, J et al. (2014) Increasing value and reducing waste in biomedical research regulation and management. Lancet 383, 176185.Google Scholar
11.Chan, AW, Song, F, Vickers, A et al. (2014) Increasing value and reducing waste: addressing inaccessible research. Lancet 383, 257266.Google Scholar
12.Ioannidis, JP, Greenland, S, Hlatky, MA et al. (2014) Increasing value and reducing waste in research design, conduct, and analysis. Lancet 383, 166175.Google Scholar
13.Glasziou, P, Altman, DG, Bossuyt, P et al. (2014) Reducing waste from incomplete or unusable reports of biomedical research. Lancet 383, 267276.Google Scholar
14.Chalmers, I & Glasziou, P (2009) Avoidable waste in the production and reporting of research evidence. Obstet Gynecol 114, 13411345.Google Scholar
15.Aryeetey, R, Holdsworth, M, Taljaard, C et al. (2017) Evidence-informed decision making for nutrition: African experiences and way forward. Proc Nutr Soc 76, 589596.Google Scholar
16.Cochrane Nutrition. Cochrane Nutrition 2018 https://nutrition.cochrane.org (Accessed January 2019).Google Scholar
17.Schwingshackl, L, Knuppel, S, Schwedhelm, C et al. (2016) Perspective: nutrigrade: a scoring system to assess and judge the meta-evidence of randomized controlled trials and cohort studies in nutrition research. Adv Nutr 7, 9941004.Google Scholar
18.Hawwash, D, Pinxten, W, Aubert Bonn, N et al. (2018) Perspective: consideration of values when setting priorities in nutrition research: guidance for transparency. Adv Nutr 9, 671687.Google Scholar
19.Rumsey, E (2016) Diet, Food, and Nutrition – How To Search in PubMed. Need to know. https://blog.lib.uiowa.edu/needtoknow/2016/03/18/food-diet-nutrition-how-to-search-in-pubmed/ (Accessed January 2019).Google Scholar
20.DIET@NET (DIETary Assessment Tools NETwork). Nutritools 2018. https://www.nutritools.org (Accessed January 2019).Google Scholar
21.World Health Organization. e-Library of Evidence for Nutrition Actions (eLENA) 2018. https://www.who.int/elena/en/ (Accessed January 2019).Google Scholar
22.World Health Organization. Global database on the Implementation of Nutrition Action (GINA) 2018. https://gdeploy.adappt.co.in/nutrition/gina/en (Accessed January 2019).Google Scholar
23.The World Cancer Research Fund International. The NOURISHING framework 2018 https://www.wcrf.org/int/policy/nourishing/our-policy-framework-promote-healthy-diets-reduce-obesity-large (Accessed January 2019).Google Scholar
24.World Health Organization. Draft Approach for the Prevention and Management of Conflicts of Interest in the Policy Development and Implementation of Nutrition Programmes at Country Level Decision-Making Process and Tool 2017. http://www.who.int/nutrition/consultation-doi/nutrition-tool.pdf (Accessed January 2019).Google Scholar
25.FAO, WHO. FAO/WHO GIFT Global Individual Food consumption data Tool. http://www.fao.org/gift-individual-food-consumption/en/ (Accessed January 2019).Google Scholar
26.Yang, C, Pinart, M, Kolsteren, P et al. (2017) Perspective: essential study quality descriptors for data from nutritional epidemiologic research. Adv Nutr 8, 639651.Google Scholar
27.Vitali, F, Lombardo, R, Rivero, D et al. (2018) ONS: an ontology for a standardized description of interventions and observational studies in nutrition. Genes Nutr 13, 12.Google Scholar
28.BioPortal. Ontology for Nutritional Epidemiology 2018. https://bioportal.bioontology.org/ontologies/ONE (Accessed January 2019).Google Scholar
29.Lachat, C, Hawwash, D, Ocke, MC et al. (2016) Strengthening the Reporting Of Observational Studies in Epidemiology-Nutritional Epidemiology (STROBE-nut): an extension of the STROBE statement. PLoS Med 13, e1002036.Google Scholar
30.STROBE-nut. STROBE-nut: An extension of the STROBE statement for nutritional epidemiology 2016. http://www.strobe-nut.org (Accessed January 2019).Google Scholar
31.Morris, SS, Cogill, B, Uauy, R et al. (2008) Maternal and child undernutrition 5 – effective international action against undernutrition: why has it proven so difficult and what can be done to accelerate progress? Lancet 371, 608621.Google Scholar
32.Rudan, I, Gibson, JL, Ameratunga, S et al. (2008) Setting priorities in global child health research investments: guidelines for implementation of CHNRI method. Croat Med J 49, 720733.Google Scholar
33.Haddad, L, Hawkes, C, Webb, P et al. (2016) A new global research agenda for food. Nature 540, 3032.Google Scholar
34.Serodio, PM, McKee, M & Stuckler, D (2018) Coca-Cola – a model of transparency in research partnerships? A network analysis of Coca-Cola's research funding (2008–2016). Public Health Nutr 21, 15941607.Google Scholar
35.Fabbri, A, Chartres, N, Scrinis, G et al. (2017) Study sponsorship and the nutrition research agenda: analysis of randomized controlled trials included in systematic reviews of nutrition interventions to address obesity. Public Health Nutr 20, 13061313.Google Scholar
36.Lachat, C, Nago, E, Roberfroid, D et al. (2014) Developing a sustainable nutrition research agenda in sub-Saharan Africa--findings from the SUNRAY project. PLoS Med 11, e1001593.Google Scholar
37.Van Royen, K, Lachat, C, Holdsworth, M et al. (2013) How can the operating environment for nutrition research be improved in sub-Saharan Africa? The views of African researchers. PLoS ONE 8, e66355.Google Scholar
38.COHRED. The Research Fairness Initiative 2016. http://rfi.cohred.org/wp-content/uploads/2015/01/Introduction-to-COHREDs-RFI_20160511.pdf (Accessed January 2019).Google Scholar
39.Balk, EM, Horsley, TA, Newberry, SJ et al. (2007) A collaborative effort to apply the evidence-based review process to the field of nutrition: challenges, benefits, and lessons learned. Am J Clin Nutr 85, 14481456.Google Scholar
40.Lawrence, M, Naude, C, Armstrong, R et al. (2016) A call to action to reshape evidence synthesis and use for nutrition policy. Cochrane Database Syst Rev 21, 11.Google Scholar
41.Guyatt, GH, Oxman, AD, Vist, GE et al. (2008) GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 336, 924926.Google Scholar
42.Cade, JE, Warthon-Medina, M, Albar, S et al. (2017) DIET@NET: best practice guidelines for dietary assessment in health research. BMC Med 15, 202.Google Scholar
43.Pijls, L, Ashwell, M & Lambert, J (2009) EURRECA – A network of excellence to align European micronutrient recommendations. Food Chem 113, 748753.Google Scholar
44.Almiron-Roig, E, Aitken, A, Galloway, C et al. (2017) Dietary assessment in minority ethnic groups: a systematic review of instruments for portion-size estimation in the United Kingdom. Nutr Rev 75, 188213.Google Scholar
45.Serra-Majem, L, Andersen, LF, Henrique-Sanchez, P et al. (2009) Evaluating the quality of dietary intake validation studies. Brit J Nutr 102, S3S9.Google Scholar
46.Chiu, K, Grundy, Q & Bero, L (2017) ‘Spin’ in published biomedical literature: a methodological systematic review. PLoS Biol 15, 9.Google Scholar
47.Kirkpatrick, SI, Collins, CE, Keogh, RH et al. (2018) Assessing dietary outcomes in intervention studies: pitfalls, strategies, and research needs. Nutrients 10, 8.Google Scholar
48.Williamson, PR, Altman, DG, Bagley, H et al. (2017) The COMET handbook: version 1.0. Trials 18, Suppl. 3, 280.Google Scholar
49.Rucker, RB & Rucker, MR (2016) Nutrition: ethical issues and challenges. Nutr Res 36, 11831192.Google Scholar
50.Weaver, CM & Miller, JW (2017) Challenges in conducting clinical nutrition research. Nutr Rev 75, 491499.Google Scholar
51.Tseng, M, Barnoya, J, Kruger, S et al. (2018) Disclosures of Coca-Cola funding: transparent or opaque? Public Health Nutr 21, 15911593.Google Scholar
52.Schwab, T (2018) Dietary disclosures: how important are non-financial interests? BMJ 361, k1451.Google Scholar
53.Bero, L & Grundy, Q (2018) Conflicts of interest in nutrition research. JAMA 320, 9394.Google Scholar
54.Enpadasi. Joint Programming Initiative – A Healthy Diet for A Healthy Life European Nutrition Phenotype Assessment and Data Sharing Initiative 2018. http://www.enpadasi.eu/deliverables_final_pdf/D51..pdf (Accessed January 2019).Google Scholar
55.U.S. National Library of Medicine. ClinicalTrials.gov.https://clinicaltrials.gov (Accessed January 2019).Google Scholar
56.World Health Organization. International Clinical Trials Registry Platform (ICTRP). http://www.who.int/ictrp/en/ (Accessed January 2019).Google Scholar
57.University of York. PROSPERO International prospective register of systematic reviews 2018. https://www.crd.york.ac.uk/PROSPERO/ (Accessed January 2019).Google Scholar
58.Institute for Health Metrics and Evaluation. Global Burden of Disease (GBD) 2018. http://www.healthdata.org/gbd (Accessed January 2019).Google Scholar
59.NCD Risk Factor Collaboration (NCD-RisC) 2018. http://ncdrisc.org (Accessed January 2019).Google Scholar
60.Global Nutrition and Policy Consortium. The Global Dietary Database 2018. https://www.globaldietarydatabase.org/the-global-dietary-database-measuring-diet-worldwide.html (Accessed January 2019).Google Scholar
61.European Commission. National Information Platforms for Nutrition. http://www.nipn-nutrition-platforms.org (Accessed January 2019).Google Scholar
62.ENPADASI. Phenotype database. https://dashin.eu/interventionstudies/ (Accessed January 2019).Google Scholar
63.Gaye, A, Marcon, Y, Isaeva, J et al. (2014) DataSHIELD: taking the analysis to the data, not the data to the analysis. Int J Epidemiol 43, 19291944.Google Scholar
64.EFSA (2015) The food classification and description system FoodEx2 (revision 2). EFSA Supporting Publications 12(5).Google Scholar
65.Pinart, M, Nimptsch, K, Bouwman, J et al. (2018) Joint data analysis in nutritional epidemiology: identification of observational studies and minimal requirements. J Nutr 148, 285297.Google Scholar
66.Noy, NF & McGuinness, DL (2001) Ontology development 101: A guide to creating your first ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880.Google Scholar
67.Ashburner, M, Ball, CA, Blake, JA et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 2529.Google Scholar
68.Moher, D, Glasziou, P, Chalmers, I et al. (2016) Increasing value and reducing waste in biomedical research: who's listening? Lancet 387, 15731586.Google Scholar
69.Schulz, KF, Altman, DG, Moher, D et al. (2010) CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. J Clin Epidemiol 63, 834840.Google Scholar
70.Moher, D, Liberati, A, Tetzlaff, J et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6, e1000097.Google Scholar
71.von Elm, E, Altman, DG, Egger, M et al. (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med 4, e296.Google Scholar
72.Equator Network. Enhancing the QUAlity and Transparency Of health Research 2018. http://www.equator-network.org (Accessed January 2019).Google Scholar
73.Bekkering, GE, Harris, RJ, Thomas, S et al. (2008) How much of the data published in observational studies of the association between diet and prostate or bladder cancer is usable for meta-analysis? Am J Epidemiol 167, 10171026.Google Scholar
74.Burrows, T, Golley, RK, Khambalia, A et al. (2012) The quality of dietary intake methodology and reporting in child and adolescent obesity intervention trials: a systematic review. Obes Rev 13, 11251138.Google Scholar
75.Gibson, C, Kirk, E, Lecheminant, J et al. (2004) Reporting quality of randomized trials in the diet and exercise literature. Obes Res 12, A66A6A.Google Scholar
76.Faber, M, Wenhold, FA, Macintyre, UE et al. (2013) Presentation and interpretation of food intake data: factors affecting comparability across studies. Nutrition 29, 12861292.Google Scholar
77.Nelson, M & Margetts, B (1997) Design concepts in nutritional epidemiology. New York: Oxford University Press.Google Scholar
78.Welch, RW, Antoine, JM, Bertam, JL et al. (2011) Guidelines for the design, conduct and reporting of human intervention studies to evaluate the health benefits of foods. Br J Nutr 106, Suppl. 2, S3S15.Google Scholar
79.Hornell, A, Berg, C, Forsum, E et al. (2017) Perspective: an extension of the STROBE Statement for Observational Studies in Nutritional Epidemiology (STROBE-nut): explanation and elaboration. Adv Nutr 8, 652678.Google Scholar
80.Jago, R & Wood, L (2016) IJBNPA in 2016: Strategy for advancing the science of behavior change in nutrition and physical activity, and associated editorial priorities. Int J Behav Nutr Phys 13, 80.Google Scholar
81.Cainzos-Achirica, M, Bilal, U, Al Rifai, M et al. (2018) Communication issues in nutritional observational research. Prev Med 115, 7682.Google Scholar
82.Brown, AW, Ioannidis, JPA, Cope, MB et al. (2014) Unscientific beliefs about scientific topics in nutrition. Adv Nutr 5, 563565.Google Scholar
83.Ioannidis, JPA (2018) Meta-research: Why research on research matters. PLoS Biol 16, e2005468.Google Scholar
84.Hughes, R, Shrimpton, R, Recine, E et al. (2011) A competency framework for global public health nutrition workforce development: A background paper. World Public Health Nutrition Association. Available at http://www.wphna.org/htdocs/downloadsapr2012/12-03%20WPHNA%20Draft%20competency%20standards%20report.pdfGoogle Scholar
85.International Food Policy Research Institute (2014) Global Nutrition Report 2014: Actions and Accountability to Accelerate the World's Progress on Nutrition. Washington, DC.Google Scholar
86.Fanzo, JC, Graziose, MM, Kraemer, K et al. (2015) Educating and training a workforce for nutrition in a post-2015 world. Adv Nutr 6, 639647.Google Scholar
87.African leaders and stakeholders renew their call for action to end hunger by 2025 (2018). https://au.int/en/pressreleases/20180129/african-leaders-and-stakeholders-renew-their-call-action-end-hunger-2025 (Accessed January 2019).Google Scholar
88.Scaling Up Nutrition (SUN) Movement (2018) Annual Progress Report. Geneva.Google Scholar
89.Editors Plos Med (2015) From checklists to tools: lowering the barrier to better research reporting. PLoS Med 12, 4.Google Scholar
90.Cochrance Linked data. Cochrane PICO Ontology. https://linkeddata.cochrane.org/pico-ontology; https://linkeddata.cochrane.org/about-site/test (Accessed January 2019).Google Scholar
Figure 0

Table 1. Developed tools to improve the quality of nutritional epidemiological research

Figure 1

Fig. 1. Integrated view of tackling waste in nutritional epidemiological research.