Adult diet in England: where is more support needed to achieve dietary recommendations?

Abstract

Background: Small-area estimation models are regularly commissioned by public health bodies to identify areas of greater inequality and target areas for intervention in a range of behaviours and outcomes. Such local modelling has not been completed for diet consumption in England despite diet being an important predictor of health status. The study sets out whether aspects of adult diet can be modelled from previously collected data to define and evaluate area-level interventions to address obesity and ill-health.Methods: Adults aged 16 years and over living in England. Consumption of fruit, vegetables, and sugar-sweetened beverages (SSB) are modelled using small-area estimation methods in English neighbourhoods (Middle Super Output Areas [MSOA]) to identify areas where reported portions are significantly different from recommended levels of consumption. The selected aspects of diet are modelled from respondents in the National Diet and Nutrition Survey using pooled data from 2008-2016.Results: Estimates indicate that the average prevalence of adults consuming less than one portion of fruit, vegetables or 100% juice each day by MSOA is 6.9% (range of 4.3 to 14.7%, SE 0.06) and the average prevalence of drinking more than 330ml/day of SSB is 11.5% (range of 5.7 to 30.5%, SE 0.03). Credible intervals around the estimates are wider for SSB consumption. The results identify areas including regions in London and urban areas in the North of England which may be prioritised for targeted interventions to support reduced consumption of SSB and/or an increase in portions of fruit and vegetables.Conclusion: These estimates provide valuable information at a finer spatial scale than is presently feasible, allowing for within-country and locality prioritisation of resources to improve diet. Local, targeted interventions to improve fruit and vegetable consumption such as subsidies or voucher schemes should be considered where consumption of these foods is predicted to be low.

Estimating Health over Space and Time: A Review of Spatial Microsimulation Applied to Public Health

“…The origins of these models are in non-spatial microsimulation in the 1950s (see Orcutt 1957 reproduced in 2007 [37]). Over the last two decades, a division has appeared between probabilistic approaches, which return slightly different results each time [21,38], and deterministic methods, which provide the same estimates if all input variables remain constant [11,12,17,19,20,22,33,34,39,40]. Synthetic reconstruction, such as the use of Monte Carlo sampling to add additional population characteristics to simulated populations in areas, appears much less frequently [14].…”

“…The majority of spatial microsimulation models are static; the aim of these models is to create a reliably estimated population dataset for one time point [9,11,12,[15][16][17][19][20][21][22][33][34][35][38][39][40]42]. The simplicity of these models with regards to temporal specificity allows users to explore research questions termed "what-if" scenario modelling.…”