No abstract

Small Island Developing States (SIDS) have high and increasing rates of diet-related diseases. This situation is associated with a loss of food sovereignty and an increasing reliance on nutritionally poor food imports. A policy goal, therefore, is to improve local diets through improved local production of nutritious foods. Our aim in this study was to develop methods and collect preliminary data on the relationships between where people source their food, their socio-demographic characteristics and dietary quality in Fiji and Saint Vincent and the Grenadines (SVG) in order to inform further work towards this policy goal. We developed a toolkit of methods to collect individual-level data, including measures of dietary intake, food sources, socio-demographic and health indicators. Individuals aged ≥15 years were eligible to participate. From purposively sampled urban and rural areas, we recruited 186 individuals from 95 households in Fiji, and 147 individuals from 86 households in SVG. Descriptive statistics and multiple linear regression were used to investigate associations. The mean dietary diversity score, out of 10, was 3.7 (SD1.4) in Fiji and 3.8 (SD1.5) in SVG. In both settings, purchasing was the most common way of sourcing food. However, 68% (Fiji) and 45% (SVG) of participants regularly (>weekly) consumed their own produce, and 5% (Fiji) and 33% (SVG) regularly consumed borrowed/exchanged/bartered food. In regression models, independent positive associations with dietary diversity (DD) were: borrowing/exchanging/bartering food (β = 0.73 (0.21, 1.25)); age (0.01 (0.00, 0.03)); and greater than primary education (0.44 (0.06, 0.82)). DD was negatively associated with small shop purchasing (−0.52 (95% CIs −0.91, −0.12)) and rural residence (−0.46 (−0.92, 0.00)). The findings highlight associations between dietary diversity and food sources and indicate avenues for further research to inform policy actions aimed at improving local food production and diet.

Approaches to synthesizing qualitative data have, to date, largely focused on integrating the findings from published reports. However, developments in text mining software offer the potential for efficient analysis of large pooled primary qualitative datasets. This case study aimed to (a) provide a step‐by‐step guide to using one software application, Leximancer, and (b) interrogate opportunities and limitations of the software for qualitative data synthesis. We applied Leximancer v4.5 to a pool of five qualitative, UK‐based studies on transportation such as walking, cycling, and driving, and displayed the findings of the automated content analysis as intertopic distance maps. Leximancer enabled us to “zoom out” to familiarize ourselves with, and gain a broad perspective of, the pooled data. It indicated which studies clustered around dominant topics such as “people.” The software also enabled us to “zoom in” to narrow the perspective to specific subgroups and lines of enquiry. For example, “people” featured in men's and women's narratives but were talked about differently, with men mentioning “kids” and “old,” whereas women mentioned “things” and “stuff.” The approach provided us with a fresh lens for the initial inductive step in the analysis process and could guide further exploration. The limitations of using Leximancer were the substantial data preparation time involved and the contextual knowledge required from the researcher to turn lines of inquiry into meaningful insights. In summary, Leximancer is a useful tool for contributing to qualitative data synthesis, facilitating comprehensive and transparent data coding but can only inform, not replace, researcher‐led interpretive work.

Objective To explore what is known on community-based food production initiatives (CFPIs) in Small Island Developing States, particularly the health, social, economic, and environmental impacts of and on CFPIs. Methods This was a systematic scoping review using 14 electronic databases to identify articles published from 1997 to 2016 on the topic of CFPIs in Small Island Developing States. From 8 215 articles found, 153 were eligible and abstracted. Analysis focused on geographic location, typology, methodology, study design, theoretical frameworks, and impacts. Results Most research was conducted in the Pacific or Caribbean (49% and 43% of studies, respectively) and primarily focused on fishing and crop farming (40%, 34%). Findings indicate a predominance of research focusing on the environmental impact of marine and coastal resources on CFPIs, and very limited evidence of CFPI impact on human health, particularly nutrition and diet-related outcomes. There was a lack of explicit theoretical frameworks to explain the impacts of CFPIs. Conclusions Evidence of impacts of CPFIs in Small Island Developing States is limited and the approaches taken are inconsistent. This review demonstrates the need and provides a basis for developing a coherent body of methods to examine the impacts of CFPIs and provide evidence to guide policy, especially as it relates to health.

BackgroundInnovative approaches are required to move beyond individual approaches to behaviour change and develop more appropriate insights for the complex challenge of increasing population levels of activity. Recent research has drawn on social practice theory to describe the recursive and relational character of active living but to date most evidence is limited to small-scale qualitative research studies. To ‘upscale’ insights from individual contexts, we pooled data from five qualitative studies and used machine learning software to explore gendered patterns in the context of active travel.MethodsWe drew on 280 transcripts from five research projects conducted in the UK, including studies of a range of populations, travel modes and settings, to conduct unsupervised ‘topic modelling analysis’. Text analytics software, Leximancer, was used in the first phase of the analysis to produce inter-topic distance maps to illustrate inter-related ‘concepts’. The outputs from this first phase guided a second researcher-led interpretive analysis of text excerpts to infer meaning from the computer-generated outputs.ResultsGuided by social practice theory, we identified ‘interrelated’ and ‘relating’ practices across the pooled datasets. For this study we particularly focused on respondents’ commutes, travelling to and from work, and on differentiated experiences by gender. Women largely described their commute as multifunctional journeys that included the school run or shopping, whereas men described relatively linear journeys from A to B but highlighted ‘relating’ practices resulting from or due to their choice of commute mode or journey such as showering or relaxing. Secondly, we identify a difference in discourses about practices across the included datasets. Women spoke more about ‘subjective’, internal feelings of safety (‘I feel unsafe’), whereas men spoke more about external conditions (‘it is a dangerous road’).ConclusionThis rare application of machine learning to qualitative social science research has helped to identify potentially important differences in co-occurrence of practices and discourses about practice between men’s and women’s accounts of travel across diverse contexts. These findings can inform future research and policy decisions for promoting travel-related social practices associated with increased physical activity that are appropriate across genders.