Use of itemized Till receipts to adjust for correlated dietary measurement error

A systematic review of supermarket automated electronic sales data for population dietary surveillance

Context

Most dietary assessment methods are limited by self-report biases, how long they take for participants to complete, and cost of time for dietitians to extract content. Electronically recorded, supermarket-obtained transactions are an objective measure of food purchases, with reduced bias and improved timeliness and scale.

Objective

The use, breadth, context, and utility of electronic purchase records for dietary research is assessed and discussed in this systematic review.

Data sources

Four electronic databases (MEDLINE, EMBASE, PsycINFO, Global Health) were searched. Included studies used electronically recorded supermarket transactions to investigate the diet of healthy, free-living adults.

Data extraction

Searches identified 3422 articles, of which 145 full texts were retrieved and 72 met inclusion criteria. Study quality was assessed using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.

Data analysis

Purchase records were used in observational studies, policy evaluations, and experimental designs. Nutrition outcomes included dietary patterns, nutrients, and food category sales. Transactions were linked to nutrient data from retailers, commercial data sources, and national food composition databases.

Conclusion

Electronic sales data have the potential to transform dietary assessment and worldwide understanding of dietary behavior. Validation studies are warranted to understand limits to agreement and extrapolation to individual-level diets.

Systematic Review Registration

PROSPERO registration no. CRD42018103470

Validity of an online 24-h recall tool (myfood24) for dietary assessment in population studies: comparison with biomarkers and standard interviews

BACKGROUND

Online dietary assessment tools can reduce administrative costs and facilitate repeated dietary assessment during follow-up in large-scale studies. However, information on bias due to measurement error of such tools is limited. We developed an online 24-h recall (myfood24) and compared its performance with a traditional interviewer-administered multiple-pass 24-h recall, assessing both against biomarkers.

METHODS

Metabolically stable adults were recruited and completed the new online dietary recall, an interviewer-based multiple pass recall and a suite of reference measures. Longer-term dietary intake was estimated from up to 3 × 24-h recalls taken 2 weeks apart. Estimated intakes of protein, potassium and sodium were compared with urinary biomarker concentrations. Estimated total sugar intake was compared with a predictive biomarker and estimated energy intake compared with energy expenditure measured by accelerometry and calorimetry. Nutrient intakes were also compared to those derived from an interviewer-administered multiple-pass 24-h recall.

RESULTS

Biomarker samples were received from 212 participants on at least one occasion. Both self-reported dietary assessment tools led to attenuation compared to biomarkers. The online tools resulted in attenuation factors of around 0.2-0.3 and partial correlation coefficients, reflecting ranking intakes, of approximately 0.3-0.4. This was broadly similar to the more administratively burdensome interviewer-based tool. Other nutrient estimates derived from myfood24 were around 10-20% lower than those from the interviewer-based tool, with wide limits of agreement. Intraclass correlation coefficients were approximately 0.4-0.5, indicating consistent moderate agreement.

CONCLUSIONS

Our findings show that, whilst results from both measures of self-reported diet are attenuated compared to biomarker measures, the myfood24 online 24-h recall is comparable to the more time-consuming and costly interviewer-based 24-h recall across a range of measures.

A comparison of dietary estimates from the National Aboriginal and Torres Strait Islander Health Survey to food and beverage purchase data

OBJECTIVE

We compared self-reported dietary intake from the very remote sample of the National Aboriginal and Torres Strait Islander Nutrition and Physical Activity Survey (VR-NATSINPAS; n=1,363) to one year of food and beverage purchases from 20 very remote Indigenous Australian communities (servicing ∼8,500 individuals).

METHODS

Differences in food (% energy from food groups) and nutrients were analysed using t-test with unequal variance.

RESULTS

Per-capita energy estimates were not significantly different between the surveys (899 MJ/person/day [95% confidence interval -152,1950] p=0.094). Self-reported intakes of sugar, cereal products/dishes, beverages, fats/oils, milk products/dishes and confectionery were significantly lower than that purchased, while intakes of meat, vegetables, cereal-based dishes, fish, fruit and eggs were significantly higher (p<0.05).

CONCLUSION

Differences between methods are consistent with differential reporting bias seen in self-reported dietary data. Implications for public health: The NATSINPAS provides valuable, much-needed information about dietary intake; however, self-reported data is prone to energy under-reporting and reporting bias. Purchase data can be used to track population-level food and nutrient availability in this population longitudinally; however, further evidence is needed on approaches to estimate wastage and foods sourced outside the store. There is potential for these data to complement each other to inform nutrition policies and programs in this population.

An overview of the state of the art of automated capture of dietary intake information

Significant benefits arise from being able to capture dietary or nutritional intake information automatically or semi-automatically. These include the ability for individuals to know and understand their nutritional intake and hence improve their diet and health. To date, only highly manual processes such as 24-hour recall, food diaries, and food journals have been utilized which have been overly cumbersome for widespread adoption. Emerging informatics, computer vision, mobile computing, and sensor-based approaches are likely to play a role in further automating the capture of dietary intake information and these are becoming increasingly utilizable through such advents as the rapid and ubiquitous uptake of smartphones with built-in digital cameras and other sensors. In this paper, we review the state of the art of technologies for automatic capture of dietary intake information and identify significant outstanding research problems and promising directions.

Healthful grocery shopping. Perceptions and barriers

While there is evidence of the factors influencing the healthfulness of consumers' food choice, little is known about how consumers perceive the healthfulness of their shopping. This study aimed to explore consumers' perceptions of, and identify barriers to, conducting a healthful shop. Using a qualitative approach, consisting of an accompanied shop and post-shop telephone interview, 50 grocery shoppers were recruited. Results showed that consumers used three criteria to identify a healthful shop: (1) inclusion of healthful foods; (2) avoidance or restriction of particular foods; and (3) achieving a balance between healthful and unhealthful foods. Those who take a balanced approach employ a more holistic approach to their diet while those who avoid or include specific foods may be setting criteria to purchase only certain types of food. The effectiveness of any of these strategies in improving healthfulness is still unclear and requires further investigation. Two barriers to healthful shopping were: (i) lack of self-efficacy in choosing, preparing and cooking healthful foods and (ii) conflicting needs when satisfying self and others. This highlights the need for interventions targeted at building key food skills and for manufacturers to make healthful choices more appealing.