OP07 Changes in the sugar content of food purchases and socio-economic inequalities: a longitudinal study of british households, 2014–2017
Bibliographic record
Abstract
Background The majority of the UK population fall short of meeting dietary recommendations. This has led to a recent policy focus on improving population diet through reducing sugar consumption. This study aims to explore whether there have been recent changes in the sugar content of take-home food and beverage purchases. We assess whether these changes differ by socio-economic position (SEP). Methods We used 2014 to 2017 data from the Kantar Worldpanel UK, a nationally representative panel study of food and beverages bought by British households and brought into the home (n≈32,000 per year). Households used hand-held barcode scanners to report purchases of over 151 million food and beverage products, for which total sugar content was obtained. We used linear mixed models to estimate annual changes in the average sugar content of daily purchases by occupational social grade (high-SEP: A/B, mid-SEP: C1/C2 and low-SEP: D/E) from 24 healthier and less healthy food groups defined using the UK Department of Health nutrient profiling model. Results were adjusted for potential socio-demographic confounders. Final sample included 282,712 quarter-observations from 28,037 households. Results Preliminary results show that in 2014, predicted average sugar content of daily purchases was 86.2 g per person (95%CI 85.3–87.0 g) in high-SEP, 87.3 g (95%CI 68.8–87.9 g) in mid-SEP, and 89.4 g (95%CI 88.7–90.2 g) in low-SEP households. By 2017, this had decreased by an average of 7.1 g per person (95%CI 6.8–7.4 g) with a greater decrease observed in low-SEP households (8.2 g, 95%CI 7.6–8.7 g) compared to mid-SEP (6.9 g, 95%CI 6.5–7.2 g) and high-SEP (6.5 g, 95%CI 5.9–7.0 g) households. This decrease is largely due to reductions in sugar purchased from less healthy food groups (incl. sugary drinks and table sugar), and was similar in magnitude across SEP households (-6.4 to -5.4 g). However, in 2017, the amount of sugar purchased from less healthy products which usually contain higher levels of added sugar was still 3.5 g (95%CI 2.7–4.3 g) higher in low-SEP compared to high-SEP households. Conclusion There has been a 7.1 g per person per day reduction of total sugar purchased to take-home between 2014 and 2017. Relatively larger reductions were observed among low-SEP households. This means that by 2017, SEP differences in the total amount of sugar purchased were no longer statistically significant. However, low-SEP households continued to purchase greater amount of sugar from less healthy products in comparison to mid- and high-SEP households. Future work should identify if these changes are triggered by consumer behaviour and/or changes in products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".