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P23 Using latent class analysis to explore dietary patterns and their associations between sociodemographic characteristics, food sources, dietary diversity, and food insecurity in small island developing states
  1. Eden Augustus1,
  2. Divya Bhagtani2,
  3. Emily Haynes3,
  4. Arlette St Ville4,
  5. Viliamu Iese5,
  6. Jioje Fesaitu5,
  7. Florian Kroll6,
  8. Ian Hambleton1,
  9. Sara Benjamin-Neelon7,
  10. Nigel Unwin2,3
  1. 1The George Alleyne Chronic Disease Research Centre, The University of the West Indies, Bridgetown, Barbados
  2. 2MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
  3. 3European Centre for Environment and Human Health, University of Exeter, Turo, UK
  4. 4Faculty of Food and Agriculture, The University of the West Indies, St. Augustine, Trinindad and Tobago
  5. 5Pacific Centre for Environment and Sustainable Development (PaCE-SD), The University of the South Pacific, Suva, Fiji
  6. 6Institute for Poverty, Land and Agrarian Studies (PLAAS), University of the Western Cape and DSI-NRF Centre of Excellence in Food Security,Cape Town 7535, South Africa
  7. 7Department of Health, Behaviour and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA


Background The high burden of disease related to malnutrition in Small Island Developing States (SIDS) has been exacerbated by increasing levels of food insecurity (FI) and loss of food sovereignty. Internationally, household, or individual level FI is associated with poorer diets and nutritional status. Our study aimed to investigate whether there are distinct dietary patterns, and if so whether they are associated with socio-demographic characteristics (SDC), dietary diversity scores (DDS), food sources and experience of food insecurity in adults in two SIDS: Fiji and St. Vincent and the Grenadines (SVG).

Methods A cross-sectional household survey was conducted, recruiting adults and adolescents (> 15 years) from 95 and 86 households in rural and urban Fiji (n=186) and SVG (n=147), respectively. Data were collected by trained interviewers using standard tools with a 24-hour recall component, adapted to the local food environments. Latent class analysis (LCA) was conducted using 13 food groups, and moderate to severe FI categories derived from the Food Insecurity Experience Scale (FIES). LCA was undertaken in R, and best fit solutions were based on the AIC results. Differences between the LCA derived classes were examined using one-way ANOVA and Pearson Chi-Squared tests.

Results In both Fiji and SVG the best fit LCA derived 3 distinct dietary patterns, across which were differences in DDS (p<0.001). In Fiji dietary patterns were associated with age (p=0.042), sex (p=0.047), and rural residence (p=0.005). In SVG there were no associations with SDCs. In both Fiji and SVG dietary patterns were associated with >weekly sourcing of food by borrowing/exchanging (p<0.001), and in both settings sourcing food in this way was most frequent in the dietary pattern with the highest DDS. In SVG >weekly sourcing food from a small shop varied by dietary pattern (p=0.002), being highest in that with the lowest DDS. In Fiji FI was associated with dietary patterns (p=0.011), ranging from 6.7% (95%CI 3.0, 14.1) to 26.5% (95%CI 14.3, 43.7). In SVG there was no apparent association between FI and dietary pattern (p=0.507), and FI in the whole sample was 35.4% (95%CI 27.6, 43.1).

Conclusion Food environment and culture likely accounts for differences across settings. However, associations were found among dietary patterns and SDC, FI and food sources in at least one setting, with sourcing food through borrowing/bartering prominent among groups in both settings, with the highest DDS. This highlights the need for further research to inform policies.

  • Latent class analysis
  • dietary patterns
  • Small Island Developing States (SIDS)

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