Linking the dimensions of policy-related research on obesity: a hybrid mapping with multicluster topics and interdisciplinarity maps
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Mapping the intellectual structure and dynamics of complex, multidisciplinary domains has long been a challenging task for bibliometrics. Research subjects with outstanding social relevance are typically of this sort, being multifaceted and requiring a synthesis of various field-specific perspectives. Among such subjects, our work addresses policy-related research on obesity, and aims to uncover how this multilevel issue is represented in policy studies through its dense thematic interrelations, and at the interfaces of various research areas participating in the discourse. In doing so, we propose an analytic framework combining so-called hybrid methods of science mapping with the (traditional) use of alluvial diagrams, resulting in what we refer to as “multicluster topics” and “interdisciplinarity maps”. Therefore, the contribution of this paper can be considered both at the subject and at the methodological level.
KeywordsScience mapping Hybrid methods Research trends Alluvial diagrams Obesity Public policy Public health Interdisciplinarity Concept maps IDR
(RQ1) How the multifaceted thematic or topical structure of obesity issues is being represented in the research on related policies (at any level of the issue where policies can be formulated)? How this thematic representation, and its structure has been developing over time? What are the major trends of this discourse?
(RQ2) Given its apparent multidisciplinarity, what research fields and areas interact in the “policy domain”, and through which topics and conceptual frameworks? What are the key concepts or themes connecting research areas, and how their role is developing over time?
(RQ3) How can we combine existing mapping techniques (in a so-called hybrid method) that (1) grasp the topical structure and its interrelations from different perspectives (according to different techniques) and (2) connect these perspectives, while (3) allow for a meaningful interpretation with transparent dimensions, and (4) for intuitive visualization providing an overview on the different aspects and their connections?
To address this methodological issue, we combined reference-analytic and text mining approaches in a framework that utilizes a simple multivariate and visualization technique, namely, alluvial diagrams. An additional experiment was to arrive at a single visualization involving a dynamic and a structural view on how the domain is developing, without separating these into different plots and diagrams.
Related work on obesity
Obesity as a research topic has attracted great attention in the scientific literature both because its complex nature and growing societal relevance worldwide. This observation also applies to secondary research designs akin to our own approach inasmuch their main objective is some synthesis or review of the domain. Various systematic reviews or metaanalyses (characteristic of the medical and health sciences fields) have been conducted on numerous aspects of obesity, even in the policy arena (such as interventions or prevention programmes). However, as our main interest was the bibliometric approach involving large-scale mapping of the discourse (as opposed to the systematic review design), we were screening the related literature for such contributions. In general, several bibliometric studies addressing the composition of obesity research (with the broadest scope of the term) and its development have been reported in field-specific venues. Khan et al. (2016) analyzed the growth of obesity literature and the collaboration patterns at the country level using the standard databases (PubMed, Google Scholar, Scopus, WoS). The growth and distributions of the research output over geographic areas, journals, research areas and languages indexed in PubMed was the subject of Vioque et al. (2010). Similar studies dealt with specific geographic regions, such as the Arab countries (Sweileh et al. 2014). These aspects were complemented with a more detailed analysis on co-author networks, journal citation networks and simple thematic maps, based on co-occurrences of frequent terms in Yao et al. (2018), also a study on a specific clinical aspect (the role of intestinal microbiota in obesity). The topical organization of (NHLBI-) funded projects and the productivity and impact of individual topics was the key issue for Nicastro et al. (2016). However, probably the most extensive approach, being also the most relevant to our present work, has been provided in a series of recent papers best exemplified by Cassi et al. (2017). The main objective of this work was a large-scale bibliometric mapping of the intellectual structure of obesity research in general, and contrasting it with the societal demands, also formalized into a topic map (based on European parliament questions) so that the concordances between the two maps could be analyzed. In other words, the relation between research questions and policy-related questions were investigated, creating close proximity to our research goals. Our work extends this line of inquiry in a different direction, focusing specifically on policy-related obesity research as a potential interface between science and public policy (as in decision making). This complementary role can also be claimed at the methodological level: the referred study used a well-known topic modelling technique (Latent Dirichlet Allocation, LDA), to cope with the complex and densely interrelated topical structure of obesity research. Here, we propose a different framework to handle thematic complexities, to accumulate further evidence on the fine-grained structure of the policy-centred subdomain.
Data and methods
To build a bibliographic database representing policy perspectives on obesity, we used the Web of Science database (WoS, Core Collection). The search strategy we employed was deliberately simple: the query targeted items containing both “obesity” and “policy” as subject terms, i.e. these terms occurring either in the title, abstract or among the keywords of document metadata (TS = ‟obesity” AND TS = ‟policy”). The reason for this simplicity in delineating the domain was to reach a core of the literature that has an explicit connection to our research goals. In particular, we wanted to cover that part of the related studies that specifically refer to obesity as a concept/phenomenon, and name some related policies. That is why other search term combinations (truncated words, variants etc.), such as obese, obes* and the like were not applied. However, we conducted a test for this search strategy, and ran an alternative strategy, using polic* instead of policy in the query. We then contrasted the retrieved set of additional documents with the results of our analysis on the original sample. This post hoc type trial is being detailed in the “Appendix” of this paper, and shows that the majority of additional documents fits into the thematic trends revealed upon the original sample, which also supports that the original sample represents some data saturation for our present purposes. To further sharpen the focus on policy-related works, some narrowing on the resulted set of Subject Categories has been applied, retaining any SCs (and its content) that presumably covered policy perspectives.
The main methodological motivation behind our study was to elaborate and explore a science mapping device that (1) allows for uncovering the complexities of our research domain, such as the relations between the thematic/topical and semantic organization of obesity policy research and its development over time, as considered from different perspectives, but (2) provides results that are transparent enough for interpretation. In other words, some ideal trade-off between the multidimensional representation and the meaningful one has been sought for. A tool called “alluvial diagram” has proven to be highly suitable to achieve this goal, and qualified as the central element used across our mapping exercises. Alluvial diagrams have already been used in bibliometric mappings. Their typical purpose is a visualization of how the topical organization of a given area of research is evolving over time, hence depicting the development of some cluster structure along the timeline, where the career and formation of individual clusters can be observed [splitting, merging, changes in size etc., cf. Bohlin et al. (2014) or Najmi et al. (2017)]. Our approach, however, utilizes alluvial diagrams in the original fashion. In a more traditional sense, alluvial diagrams can be conceived as a type of multivariate analysis, by means of which the joint distribution of cases along multiple (typically categorical) variables can be described and visualized. In other words, the unique associations of categories through multiple variables can be grasped, together with their relative frequencies in the sample. Therefore, it is a natural way of analyzing a set of publications along various dimensions using alluvial diagrams, showing the interrelations between the selected aspects of analysis. Moreover, if we select the time dimension as one of these variables (the year/period of publication for documents in the set), we can outline the time dynamics of the associations between the other selected variables, the latter covering, for instance, the different aspects of topical organization. In such a way, we can obtain a complex picture of how a research domain is evolving. Hence, the core of our mapping procedure was to construct alluvials that reveal the linkages between the timeline and the various interrelated characteristics of obesity policy research obtained from our analyses. These analyses are summarized in the next sections.
Alluvial diagrams as multicluster topic development
Leveraging on the virtue of alluvials to represent multiple characteristics and their interrelations “at a glance”, we applied two different bibliometric document clustering methods to elicit the thematic structure of the research domain. The main idea was to model topical organization from different perspectives, and linking them together (and with the time dimension). As a way of “triangulation”, we selected methods that rely on differing indicators of document content, and are simple enough in themselves to keep the formation of dimensions transparent for interpretation.
Clusterings used in the mapping procedure
We used classical bibliographic coupling (BC-clustering), as a link-based method, and a clustering over semantic similarities (Kw-clustering), as a text-based method. By virtue of this dual approach, our exercise could be viewed as utilizing a “hybrid method” for document clustering [where link-based and text-based methods are being combined for higher precision, cf. Boyack and Klavans (2010)], although with a significant alteration (see below). The two clustering procedures are detailed below.
Text-based method as a different perspective on the thematic structure of our domain, we applied a measure of textual similarity as well. To that end, we employed the keywords of documents attributed by authors (author keywords, the field labelled with “DE” in the WoS databases). Despite the well-known indexer effect as a major criticism of the use of author keywords, we were expecting an acceptable level of representation of the most relevant concepts in this domain, that is suitable for complementing the link-based results. The clustering procedure consisted of the following steps. (1) Author keywords have been retrieved from documents, and subjected to a standard normalization procedure (minimal version of natural language processing) via word stemming. (2) Documents have been represented as vectors of these stemmed keywords, based on which their pairwise similarity was calculated. The measure applied in this case was Salton’s cosine similarity, as a broadly used normalized indicator for comparing word vectors for their similarity in document clustering. (3) From the similarity matrix, a (textual) similarity (or proximity) network of documents was created, and the actual clustering exercise was identical to the one used for the link-based method: the fast-greedy algorithm has been run over the proximity network to gain coherent groups of papers (in terms of keyword usage).
Interpretation and labelling of clusters
A crucial point in our approach to link different thematic perspectives was the interpretation of the topical or semantic clusters obtained from the various classifications. As with the clusterings, we addressed this task from different angles: (1) we characterized the clusters with the most frequent title words occurring in the title of papers belonging to the cluster, and (2) obtained the most representative papers of clusters, using the so-called “core documents” methodology (see below).
As to the first method (1), for each group (BC-clusters and Kw-clusters) title words have been stemmed, and those pertaining to the (inverted) first quartile of the frequency distribution of words within the cluster were kept as eligible for labelling. Using title words provided the advantage to have a semantic descriptor for the groups independent of the descriptors underlying group formation (references, keywords), and commonly used for both clusterings.
For triangulation, (2) a second round of labelling was achieved by using the “core documents” methodology as proposed by Glänzel and Thijs (2012). According to their definition, core documents are those elements of the cluster that “have at least n > 0 links of at least a given strength r ∈ (0, 1) according to the predefined similarity measure”. That is, these are “similar enough” to most papers in the cluster, given the thresholds (n, r) being set properly. We determined these parameters clusterwise, so that a paper had to be similar to at least 40–60% of the cluster in order to belong to the core, with a similarity value above the third quartile of the distribution of similarities (upon which the clustering was achieved). The experimentation resulted in a reasonable number of core documents somewhat proportional to the cluster size (see “Results and discussion” section). To further sharpen the meaning of clusters, we coded the core documents for their characteristic terms (with the help of two field experts among the authors of this paper), and applied this term set in the labelling of clusters.
Based on the results of these two methods, labelling was done manually by outlining the most common theme unifying the cluster. The interpretation of the labels was validated by two field experts among the authors of the present work. In practice, the two aspects effectively complemented each other in identifying common topical dimensions.
Among the methodological advantages of this framework, we can consider the following. As is the case with hybrid methods, our approach sets out a multidimensional mapping of the domain, relying on multiple descriptors of publications. However, unlike the methods introduced so far, that combine the different types of link-based and textual similarities via a composite measure (Janssens et al. 2009), we connect different similarity structures by linking, instead of combining them together. Consequently, it does not yield a unique or “consensus” classification of publications into topics, but a multidimensional classification where the individual dimensions are linked and kept transparent. It might be more difficult to interpret, but, in exchange, requires no subjective decision on, or experimentation with trade-offs in setting the weight of different similarities in the composite measure. Also, loss of information due to dimension reduction is much less an issue. Still, with the interrelations of perspectives coded by the joint distribution of papers over multiple category systems a well-defined classification can be drawn.
Another feature we consider valuable in this framework is its rich potential to express thematic relations. First of all, in aligning two types of classifications one can be used to validate the other (high concordance between classifications or semantic similarity). Also, a more granular classification can further stratify the results of a more robust one, introducing hierarchic relations into the thematic structure. What’s more, the explicit categories yielded by the text-based method may be used as a semantic or conceptual characterization of the link-based categories, given their linkages. Perhaps more importantly, however, this kind of projection of the semantic dimension onto the link-based dimension allows for the discovery of several kinds of overlaps between topics. Although the individual clusterings does not handle topical overlaps, as popular topic detection techniques such as LDA, their interrelations do. A connection between two link-based cluster and a semantic cluster indicates their conceptual or thematic intersection, or, conversely, a conceptual system connecting differing research traditions (link-based clusters). On our account, the potential to reveal such complexities is an important strength of the alluvials-based approach.
Alluvial diagrams as interdisciplinarity maps
Results and discussion
Basic statistics of the bibliographic record
Summary statistics of the publication output by time period
The most frequent journal titles with the total number of published papers
BMC PUBLIC HEALTH
PUBLIC HEALTH NUTRITION
AMERICAN JOURNAL OF PREVENTIVE MEDICINE
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
AMERICAN JOURNAL OF HEALTH PROMOTION
FUTURE OF CHILDREN
The frequency of occurrence of Web of Science Subject Categories (type: n ≈ 240) in the corpus
Public, Environmental & Occupational Health
Health Care Sciences & Services
Nutrition & Dietetics
Business & Economics
Education & Educational Research
Biomedical Social Sciences
General & Internal Medicine
Environmental Sciences & Ecology
Social Sciences—Other Topics
Food Science & Technology
The multidimensional characterization of thematic development
Cluster IDs and labels of clusters resulted from the bibliographic coupling (BC; keyword profiles for the clusters are reported in the “Appendix”)
Economic implications of obesity (as a societal phenomenon)
Interventions and particular, community-based programmes (especially for childhood obesity)
Risk factors of childhood obesity
Economics of food policies (food policy, farm policy, taxation, public economic policy on consumption)
Physical activity, health promotion means (environmental, and lifestyle-related)
Food marketing and communication policies, consumer behavior
School nutritional policies and instruments, competitive and healthy nutrition
Trade and globalization effects (disease, transition)
Ethnic/ratial factors of obesity (especially in children) and health disparities
Study of internet behavior in obesity research
Cluster IDs and labels of clusters resulted from the semantic similarity network (Kw; keyword profiles for the clusters are reported in the “Appendix”)
Physical activity, built environment and active living
Public health policies and obesity prevention
Risk factors of overweight, children
Food environment in school nutrition
Childhood obesity prevention, active living and community-based instruments
Ethical aspects of obesity interventions and implications
Economic and social effects of (population-level) obesity
Policy in general
Measurement of obesity
Confusion matrix of the two clusterings (Kw vs. BC-clusters)
In order to provide an overall quantitative evidence for the concordance, we have calculated the Rand index between the two groupings. The Rand index (abbreviated here as R) is a statistical measure of the similarity between two clusterings of the same dataset (the technical definition is given in the “Appendix”), and its value ranges between [0, 1]. The closer its value to the possible maximum, R = 1, the better the agreement between the two groupings. For our classifications, we obtained a value of R = 0.7 as the degree of similarity between the BC- and Kw-clustering, which, being close enough to unity, is generally considered to be a sign of good alignment.
Beyond the correspondence between the classifications, the next important observation (via the three-way diagrams) is that almost all topics are concentrated in the last 10-year period, and that almost all topics show an increase (in size) in the last 5 years, so that an upward trend emerges for the whole topical structure. This is very much in line with the rising curves obtained for publication numbers for this period, showing that this increase is multidirectional, covering a diverse and balanced thematic composition of this output.
Qualitatively, or content-wise, in order to elicit the thematic development of our domain, we follow the strategy of interpreting each multicluster topic relying on the interrelations of BC and Kw clusters (i.e. interpreting the two-way alluvial diagram using the cluster labels), and then linking them to the time dimension (i.e. via the three-way alluvial diagrams). The most salient BC cluster, #3 on risk factors of childhood obesity is mostly linked to the Kw cluster #3 on risk factors of overweight, children, and, to a smaller extent, to Kw #2 on public health policies and obesity prevention. The topic is constantly present since 2007, but increases its weight in the last five decades. The second biggest BC cluster, #6 focusing on physical activity and health promotion has a similarly strong affiliation with a specific Kw cluster, #1 on physical activity, built environment and active living, but this topic is somewhat more stratified, as BC#6 is, to a letter extent, also connected to Kw#2 (prevention) and Kw#3 (overweight). This topic is also abundant in the last decade, but reaches a higher volume in the recent period (with all subtopics). This high level of concordance can also be observed between BC#4 on economics of food policies (food policy, farm policy, taxation, public economic policy on consumption) and Kw#4 on food environment in school nutrition, where smaller proportions of the BC cluster are again linked to two further Kw blocks (Kw#2 on prevention and Kw#3 on overweight). Its subtopics mostly pertain to the last 5-year period, while the first appearance of the major subtopic (food environment) is in the previous interval. Screening the diagrams further, BC#7 with food marketing and communication policies, consumer behavior tends to be divided between several Kw clusters,—resulting in a semantically multifaceted topic—including Kw#2 (prevention) and Kw#4 (food environment) as the more prevalent subtopics, as well as Kw#3 (overweight) and Kw#5 (Childhood obesity prevention, active living and community-based instruments), in smaller proportions. The rather complex topic is clearly a product of the last period, within which it is equally distributed between the consecutive years. Cluster BC#8 on School nutritional policies and instruments, competitive and healthy nutrition closely resembles BC#7 in its semantic composition, with an even more equal distribution among the same Kw clusters (Kw#2, Kw#4, Kw#5, Kw#3), and with its subtopics also concentrated in the most recent period, as a relatively new topic. The last two prominent BC clusters (similar in terms of size) constitute a topic with one or two Kw clusters: BC#5, food environment, is practically aligned with Kw#4 (food environment in school nutrition)—aside from some subtopics being classified under Kw#3 (overweight) and Kw#2 (prevention), whereas BC#2 on interventions and particular, community-based programmes (especially for childhood obesity) has weak connections to Kw#2 and Kw#5, that is, the cluster on childhood obesity prevention, active living and community-based instruments, respectively. Again, both topics, BC#5 and BC#2 expands in the last 5-year interval (being concentrated mostly in most recent 3-year period).
Dominant topical structure of the domain: summary of the semantic concordances between BC-clusters and Kw-clusters
Risk factors of childhood obesity (2)
Risk factors of overweight, children (3); public health policies and obesity prevention (2)
Physical activity, health promotion (6)
Physical activity, built environment and active living (1); public health policies and obesity prevention (2); risk factors of overweight, children (3)
Economics of food policies (food policy, farm policy, taxation, public economic policy on consumption) (4)
Food environment in school nutrition (4); public health policies and obesity prevention (2); risk factors of overweight, children (3)
Food marketing and communication policies, consumer behavior (7)
Food environment in school nutrition (4); public health policies and obesity prevention (2)
School nutritional policies and instruments, competitive and healthy nutrition (8)
Food environment in school nutrition (4); public health policies and obesity prevention (2)
Food environment (5)
Food environment in school nutrition (4); public health policies and obesity prevention (2); risk factors of overweight, children (3)
Interventions and particular, community-based programmes (especially for childhood obesity) (2)
Public health policies and obesity prevention (2); childhood obesity prevention, active living and community-based instruments (5)
Upon this overview of the resulted structure, several observations can be made. Firstly, the two clusterings (topics and subtopics) show a fairly coherent thematic picture, with subtopics fitting into, and elaborating on the meaning of general topics. Secondly, although the whole spectrum of factors and determinants of obesity, both at the individual (e.g. dietary patterns) and various community and economic levels (sociodemographic factors, schools, education, consumption etc.), can be seen as continuously trending, the dominant theme associated to most factors is that of food environment, and school-related issues. This two general theme seems to be the main focus of recent approaches to obesity form policy perspectives. These themes relating various BC-clusters also provides evidence that the topics are densely overlapping. This interrelatedness is further confirmed by the other (semantically defined) subtopics being common to many research directions (BC-clusters). Finally, some small BC- and Kw-clusters are underrepresented in the alluvials, showing scarce connections (under the thresholds set for stripes be visible), such as the quite coherent BC-theme on trade and globalization as a factor of obesity as a global disease (#9), or the very small but distinctive BC-cluster on internet behavior (#11). This fact underlies the role of the original clusterings to complement the “dominant” structure outlined by cluster interrelations.
Key concepts connecting research fields: interdisciplinarity and its development
The list and indicators of key concepts identified for the interdisciplinarity maps
In what follows, we will interpret the alluvial diagrams starting with the concept group contributing most to the multidisciplinarity of our domain (highest diversity values), which is practically the first column of Table 8. Filtering out the general themes (health, public health, nutrition, health policy etc.) we are left, in approx. the order of frequencies, with “obesity indicators” (body mass index, overweight), children as distinguished target group (childhood obesity, children, parent, and we can assign to this thematic axis adolescent as well), food policies (food policy, food, diet), and some prevalent factors and risks or regions of interest (socioeconomic status, diabetes, China, respectively). Concepts in the second column can be roughly assigned to these categories (see the detailed overview below), except physical activity, which is the most frequent key concept in the list, deserving a separate description.
Consulting the alluvials (Fig. 6), obesity indicators seem to serve as a common language among fields, connecting mainly Nutrition and Dietetics (through overweight but not the BMI, interestingly) and Pediatrics with Business and Economics and the Biomedical Social Sciences, but with stronger presence in the previous than in the most recent periods.
Childhood obesity and the related terms also link Business and Economics or Educational Sciences with Pediatrics, Nutrition and Health Care Sciences and Services with a constant prevalence in the last decade. The connecting role of parent is more extensive and latent, encompassing most areas with low frequencies per field, as shown in Fig. 7, but increasing its presence in the most recent period. On the other hand, school, while being a bridge between educational, clinical, nutritional and pediatric fields, mostly appears in between 2008 and 2013, which signals some shift of emphasis from institutional to family-related factors of childhood obesity.
Food policy as a term is rooted both in Business and economics and Agriculture, but seems more timely in connection with Nutrition and Dietetics, as the former stripes connect to only earlier periods. Fast food also appears as a less timely concept from mainly Business and Economics. Food environment, however, as a bridge between Education studies and Nutrition is a more recent framing of this perspective on obesity (linking to the latest period), while diet connects most fields (clinical, social and economic sciences) and concentrated in the last time interval. Sugar-sweetened beverages, as a specificity of this category generating much attention, is again a constant and highly multidisciplinary topic.
Physical activity is a prevalent concept in terms of size, and links the educational, clinical and health-related categories with pediatric issues. Its presence is continuous over time up to the very recent years. On the other hand, physical education is only attached to Educational Research (at least in the main trend diagram) with a similar distribution over the timeline.
Prevalent factors and risks of obesity exhibit a more subtle role in connecting areas, as the previous “massive” conceptual structures, in that many of them only expressed in the diagrams with latent connections (Fig. 7). Socioeconomic status as a key concept is equally present in all fields, and in the last decade, though with much lower frequency as per subject area. Diabetes behaves the same way, somewhat increasing its weight only within Nutrition in the last period. Distinctive in this respect is the concept of health disparities, at the intersection of Educational Research, Health Care Sciences, Nutrition and Pediatrics, as it connects these areas clearly in the most recent period. In contrast, nutrition transition and environment link most areas but in a less timely fashion. Finally, as a single concept signalling a joint attention on a geographic aspect of obesity policy, China has its related fields divided along the timeline, with an earlier contribution from Business and Economics, Agriculture and Biomedical Social Sciences, and with a most recent interest from clinical, health and nutritional sciences (G&IM, HCS&S, Nt&D).
In the present study we addressed the changing conceptualization of the complex and multilevel issue of obesity in policy-related research, uncovering its topical organization from different perspectives, and at the interfaces of the various research areas participating in the discourse. To this end, we proposed a science mapping framework utilizing hybrid (text-based and link-based) techniques, and deploying alluvial diagrams in mapping the interrelations between the different thematic perspectives, key concepts, research areas and their development over time. The two mapping approaches, the detection of “multicluster” topics and key concepts connecting research areas yielded quite convergent results: the topical structure and conceptual focus in the last 10 years appears to remain highly balanced with almost all topics and concepts getting more and more attention. The rich semantic overlaps between topics and the key concepts connecting clinical, economic, social, agricultural etc. sciences provide evidence for the high interconnectedness and common focus within the domain. There is a clear agreement between the results of both mappings that it is the themes of food environment and childhood obesity that connect the most thematic blocks and field-specific approaches (though the multicluster view picture school-related issues as constantly on the surface, for key concepts there seems to be a shift of emphasis towards family-related factors, such as the role of parents). The topics emerged in our mapping are also comparable to those identified in Cassi et al. (2017) as “social issues”/”social environment”, which is fairly acceptable for studies with a policy focus. On the other hand, there seems to be an increasing contribution from individual health-related fields, with closer proximity to the clinical sciences, viz. nutrition and dietetics to the policy discourse.
The usefulness of this dual mapping for understanding obesity-related policy research is mainly manifested in the insights gained into the latent thematic stratification of the domain. Obesity as a research topic has attracted great attention in the scientific literature both because its complex nature and growing societal relevance worldwide. It is a research subject with outstanding social relevance, being multifaceted, has various interacting social strata, and requires a synthesis of various field-specific perspectives. As such, it is especially difficult and challenging to tackle for policy-makers. To best address this challenge, the mapping reported here provides an overview of how the thematic and disciplinary structure of obesity issues is being represented in the research on related policies. It has been made explicit that, as the most general structure of the discourse, the central issue of childhood obesity is mainly contextualized, through its risk factors, at the local level of school nutrition, education, related interventions and local food environments, as well as at the national and global levels of food policies, food markets, health disparities, global deseases and food-related communication. The other pillar of this context is the issue of physical activity and health promotion, which is strongly linked, beyond health promotion means, to the interrelated topics of the built environment and lifestyles.
In terms of the proposed methodology, the alluvial-based framework, combined with a hybrid mapping, has proven to be efficient in relating different thematic classifications, as providing a mutual validation and stratification between them, expressing thematic overlaps, and their unfolding over time.
Open access funding provided by Library and Information Centre of the Hungarian Academy of Sciences (MTA KIK). This research has been supported by Food Science doctoral school of Szent Istán University and Research fond No. EFOP-3.6.3-VEKOP-16-2017-00005.
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