Background: Guidelines recommend reducing saturated fat (SFA) intake to decrease cardiovascular disease (CVD) risk, but there is limited evidence on scalable and effective approaches to change dietary intake, given the large proportion of the population exceeding SFA recommendations. We aimed to develop a system to provide monthly personalized feedback and healthier swaps based on nutritional analysis of loyalty card data from the largest United Kingdom grocery store together with brief advice and support from a healthcare professional (HCP) in the primary care practice. Following a hybrid effectiveness-feasibility design, we tested the effects of the intervention on SFA intake and low-density lipoprotein (LDL) cholesterol as well as the feasibility and acceptability of providing nutritional advice using loyalty card data. Methods and findings: The Primary Care Shopping Intervention for Cardiovascular Disease Prevention (PC-SHOP) study is a parallel randomized controlled trial with a 3 month follow-up conducted between 21 March 2018 to 16 January2019. Adults ≥18 years with LDL cholesterol >3 mmol/L (n = 113) were recruited from general practitioner (GP) practices in Oxfordshire and randomly allocated to "Brief Support" (BS, n = 48), "Brief Support + Shopping Feedback" (SF, n = 48) or "Control" (n = 17). BS consisted of a 10-minute consultation with an HCP to motivate participants to reduce their SFA intake. Shopping feedback comprised a personalized report on the SFA content of grocery purchases and suggestions for lower SFA swaps. The primary outcome was the between-group difference in change in SFA intake (% total energy intake) at 3 months adjusted for baseline SFA and GP practice using intention-to-treat analysis. Secondary outcomes included %SFA in purchases, LDL cholesterol, and feasibility outcomes. The trial was powered to detect an absolute reduction in SFA of 3% (SD3). Neither participants nor the study team were blinded to group allocation. A total of 106 (94%) participants completed the study: 68% women, 95% white ethnicity, average age 62.4 years (SD 10.8), body mass index (BMI) 27.1 kg/m2 (SD 4.7). There were small decreases in SFA intake at 3 months: control = −0.1% (95% CI −1.8 to 1.7), BS = −0.7% (95% CI −1.8 to 0.3), SF = −0.9% (95% CI −2.0 to 0.2); but no evidence of a significant effect of either intervention compared with control (difference adjusted for GP practice and baseline: BS versus control = −0.33% [95% CI −2.11 to 1.44], p = 0.709; SF versus control = −0.11% [95% CI −1.92 to 1.69], p = 0.901). There were similar trends in %SFA based on supermarket purchases: control = −0.5% (95% CI −2.3 to 1.2), BS = −1.3% (95% CI −2.3 to −0.3), SF = −1.5% (95% CI −2.5 to −0.5) from baseline to follow-up, but these were not significantly different: BS versus control p = 0.379; SF versus control p = 0.411. There were small reductions in LDL from baseline to follow-up (control = −0.14 mmol/L [95% CI −0.48, 0.19), BS: −0.39 mmol/L [95% CI −0.59, −0.19], SF: −0.14 mmol/L [95% CI −0.34, 0.07]), but these were not significantly different: BS versus control p = 0.338; SF versus control p = 0.790. Limitations of this study include the small sample of participants recruited, which limits the power to detect smaller differences, and the low response rate (3%), which may limit the generalisability of these findings. Conclusions: In this study, we have shown it is feasible to deliver brief advice in primary care to encourage reductions in SFA intake and to provide personalized advice to encourage healthier choices using supermarket loyalty card data. There was no evidence of large reductions in SFA, but we are unable to exclude more modest benefits. The feasibility, acceptability, and scalability of these interventions suggest they have potential to encourage small changes in diet, which could be beneficial at the population level. Trial registration: ISRCTN14279335.
Author summary: Why was this study done?: Cardiovascular disease (CVD) is the leading cause of death in the UK and is strongly influenced by diet composition. Reducing the intake of saturated fat (e.g., fats from animal sources such as butter or meat), mostly by swapping some key foods in the diet for others that are lower in saturated fat (SFA), can help reduce the "bad" low-density lipoprotein cholesterol (LDL-C) in the blood, and reduce the risk of CVD. Previous studies have achieved success either by providing particular foods to people or by giving them intensive support and advice from nutrition specialists. Currently, there are no practical interventions shown to help large numbers of people improve their diet to reduce the amount of saturated fat they eat. What did the researchers do and find?: In this study, we developed a system to provide regular information on the saturated fat content of food purchases and suggest healthier swaps using loyalty card data from the UK largest grocery store. Participants received brief oral and written advice from a healthcare professional (HCP) at their general practitioner (GP) practice alone or in combination with personalized feedback on their food shopping. Our primary aim was to test whether this approach was effective to decrease saturated fat intake compared with usual care, which does not involve any specific advice. We also compared changes in LDL-C and the quality of the grocery shopping. We recruited adults who had a blood test showing they had raised LDL-C from GP practices in Oxfordshire (UK), and we followed them for an average of 3.8 months. We found small decreases in SFA intake as well as the SFA content of food purchases and reductions in LDL-C, but these changes were not significantly different from those observed in the control group. Participants reported positive feedback regarding the brief advice and the personalized feedback on their food shopping, which they received monthly throughout the study. What do these findings mean?: Previous studies have shown that self-monitoring and feedback are effective strategies to help people change their behavior. In this study, we were able to use data from supermarket loyalty cards to provide regular feedback and healthier swaps to help people improve the quality of their grocery shopping. Participants valued and used this information together with the brief advice received from primary care practitioners to reduce their saturated fat intake. The trial was designed to detect a clinically significant difference in SFA intake between groups of 3%, and the intervention did not achieve such large effects. However, modeling studies suggest that just replacing 1% of saturated fat with polyunsaturated fat can potentially lead to an 8% reduction in CVD events. With future development and testing, this may be an intervention that could be offered by supermarkets to achieve small improvements in diet with population-level health benefits.
A diet high in saturated fatty acids (SFA) elevates low-density lipoprotein cholesterol (LDL-C) and increases the risk of cardiovascular disease (CVD) [[
Food purchased to prepare and eat at home comprises the majority of food consumed in most countries, and interventions targeting the nutritional quality of food purchases could improve diet quality, especially among those motivated to change [[
Building on what is known, but with a specific focus on scalability and sustainability, we developed a behavioral intervention to reduce SFA consumption using data collected through a supermarket loyalty card. Loyalty cards recording food purchases are operated by many major retailers and offer the opportunity to provide personalized dietary interventions at scale. We tested the intervention among patients in primary care with raised LDL-C who received additional motivation to change and brief advice from a healthcare professional (HCP) in a short counselling session. Following a hybrid effectiveness-feasibility design [[
The Primary Care Shopping Intervention for Cardiovascular Disease Prevention Study (PC-SHOP) was a randomized, 3-arm parallel controlled open-label trial with blinded assessment of the primary outcome. Participants were individually randomized to either the control group or one of 2 active interventions for 3 months after giving written informed consent to participate in the study.
This study was reviewed and approved by the National Health Service Health Research Authority (HRA) Research Ethics Committee (Ref: 17/SC/0168). The trial protocol includes further information regarding the trial design and interventions [[
Four primary care practices in Oxfordshire, UK, near the participating supermarket were selected so it was more likely that potential participants shopped at this store. General practices sent invite letters to patients who were aged ≥18 years and with a recorded LDL cholesterol >3.5 mmol/L or total cholesterol >5.5 mmol/L in the previous 5 years. Eligible participants were adults aged ≥18 years; with a baseline LDL ≥3 mmol/L on retesting; willing to make changes to their diet in order to reduce CVD risk; who had responsibility for the majority of the household food/grocery shopping (e.g., complete at least half of their household shopping); who usually shop at the collaborating grocery store (at least every 2 weeks in store and/or online); with a loyalty card registered exclusively under their name before recruitment; with access and ability to use a computer with internet connection; and willing and able to give informed consent for participation in the study. During screening, we excluded people with a self-reported recent incident of CVD, recent or planned changes to lipid medications, or those taking part in other relevant research. Interested and potentially eligible people were invited to a baseline appointment with the study team at their general practice to discuss and agree to participate and check eligibility again. People who who failed to complete the 2 baseline dietary assessments were excluded (Fig 1, CONSORT diagram; S2 Appendix, List of inclusion and exclusion criteria).
Graph: Fig 1 CONSORT flowchart.CONSORT, Consolidated Standards of Reporting Trials; LDL-C, low-density lipoprotein cholesterol.
Participants were individually randomized in a 1:3:3 ratio, to either the control group or one of 2 active interventions. A computer-generated randomization sequence was generated by an independent statistician using fixed block sizes of 7 with random order. After enrollment, participants' allocation to each trial arm was revealed to the researchers using an online program (RedCap, https://
The brief advice component of the interventions meant that it was impossible to fully blind HCPs, but they remained blind to which of the 2 active intervention groups the participant was allocated. Likewise, participants could not be blind to allocation, and there were insufficient research staff to blind them to allocation at follow-up when some of the clinical measures (secondary outcomes) were taken. The primary outcome was saturated fat intake collected through a web-based questionnaire, which individuals completed without involving the study team and was analyzed blind by an independent statistician.
Details of the active interventions and their theoretical framework can be found in the protocol [[
Participants allocated to the SF intervention also received a report on the saturated fat in their household grocery store food purchases during the intervention period. The study team received data from the participating supermarket each week and generated and sent participants a personalized shopping report on purchases in the preceding period using supermarket loyalty card data, at baseline and at the end of the first, second, and third month of the intervention period. The shopping reports provided information on the mean weekly saturated fat content of their food shopping, identified 5 major contributors to SFA intake over the previous period, as well as suggestions for one-for-one swaps to foods containing less SFA but with similar functional characteristics. Participants were encouraged to use the monthly reports to guide their shopping list and to monitor their progress in reducing SFA. Details of the approach and algorithm to generate personalized shopping advice can be found elsewhere [[
Participants in the control group received no intervention. They were informed of the results of their blood tests by post and invited to a further check after 3 months (end of follow-up period).
Brief advice session with a nurse or healthcare assistant at the GP practice.
- Single 10-minute appointment.
- Written materials: British Heart Foundation "Cut the Saturated Fat" leaflet and NHS Choices information together with blood results.
Personalized shopping report.
- One report per month from baseline to follow-up (up to 4 reports in total, print form and email) containing information on weekly amount of saturated fat in shopping, top 5 food contributors to saturated fat plus lower saturated fat swaps to foods with similar functional characteristics.
Participants were asked to complete a computerized 24-hour dietary recall prior to the baseline visit and a second one at the baseline visit. Participants provided their supermarket loyalty card number and consent to access information on all food purchases from 6 months before baseline until the end of the study. Trained researchers measured weight, height, blood pressure, and collected demographic information and relevant medical history and medications. A fasting capillary blood sample was collected and analyzed using a point of care device (Alere Cholestech LDX) to determine total cholesterol, high-density lipoprotein cholesterol (HDL-C), LDL-C, and triglycerides. After randomization, participants in BS and SF groups met with a HCP for the brief advice session.
A single follow-up visit took place 3 months later, repeating the baseline measures (except height) and including an additional questionnaire assessing the acceptability of the intervention.
Individual self-reported dietary intake was assessed using the validated questionnaire, the Oxford Biobank WebQ, which collects information on the quantities of all foods and beverages consumed over the previous day [[
Shopping data on all recorded food purchases from 6 months before baseline and during the study were also used to evaluate the effect of the intervention given the high correlations found with dietary intake measurements [[
The primary outcome was the change in reported saturated fat intake (%SFA) measured on 2 days at baseline and again at follow-up. The full list of prespecified secondary and nonefficacy outcomes included changes from baseline to follow-up in SFA (kcal), total energy intake (kcal), total fat (kcal, %EI), total sugars (kcal, %EI), fiber (g/100 kcal), and key food groups (%EI). Other exploratory outcomes from the dietary measurements were changes in total monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) intakes between baseline and follow-up. Prespecified secondary outcomes from food purchases included changes from baseline to follow-up in SFA (%TE; kcal per £), total fat and sugars (%TE; kcal per £), salt (g/100 g), cost (£/week and £/Kg), energy density (kcal/g), and key food groups (%TE) expressed as percentages to be comparable between the diet and the shopping data. We also assessed changes in LDL-C, HDL-C, total cholesterol, and triglycerides.
For the process evaluation, we assessed the feasibility of recruitment and follow-up by measuring the number of participants who accepted the invitation and consented to take part as well as the number of participants that completed follow-up. We measured acceptability of the intervention through nonvalidated questionnaires completed at baseline and follow-up (rated on a scale 1–5 from least to most helpful, S3 Appendix). The fidelity of the intervention delivery by the HCP was measured through the analysis of audio-taped sessions.
We powered the study to detect a difference in %SFA reduction of 3% (3% SD) between each intervention group and control, which was considered plausible based on previous interventions [[
After the statistical analysis plan was approved by the trial management group and an independent statistician, the database was locked, and the statistical analysis plan was implemented without changes to the primary or secondary outcome analyses. The results of the trial were computed as comparative summary statistics by group (difference in means between baseline and follow-up, 95% CIs), and the primary comparisons between groups were analyzed with a linear regression model with adjustment for GP practice and baseline values. Prior to analysis, assumptions of linear regression (normality of residuals, homogeneity of variances, and outliers) were tested and met. Information on the acceptability of the intervention was collected by questionnaire and summarized by presenting the frequencies of each response.
We performed prespecified sensitivity analyses to assess the impact of missing data on the primary outcome, including using baseline observation carried forward, as well as excluding people with only one dietary recall or excluding specific days with reported dietary intakes reflecting implausible habitual intake (<500 kcal/day or >3,500 kcal/day [[
Participants were recruited from 4 GP practices in Oxfordshire between 21 March 2018 and 10 October 2018. A final sample of 113 were randomized to either "No intervention" (n = 17), "BS" (n = 48) or "SF" (n = 48). Follow-up was completed on 16 January 2019, and 106 (94%) participants completed the study after an average of 115 days (SD 26, minimum 77, maximum 208) (Fig 1).
Participants were mostly women (68%), of white ethnicity (95%), with average age of 62.4 years (SD 10.8), and BMI 27.1 kg/m
Graph
Table 1 Baseline characteristics of participants assigned to interventions or control.
Total ( Control ( Brief Support ( Brief Support plus Shopping Feedback ( Mean/ SD/% Mean/ SD/% Mean/ SD/% Mean/ SD/% Age, years, mean (SD) 62.4 10.8 62.9 11.2 64.7 9.2 59.9 11.7 Gender, female 77 68.1 11 64.7 34 70.8 32 66.7 BMI, kg/m2, mean (SD) 27.1 4.7 26.0 5.1 26.8 4.0 27.8 5.2 BMI categories Normal weight (18.5–24.9) 38 33.6 7 41.2 14 29.2 17 35.4 Overweight (25–29.9) 53 46.9 8 47.1 27 56.3 18 37.5 Obesity (≥30) 22 19.5 2 11.8 7 14.6 13 27.1 Blood pressure, mean (SD) Systolic, mmHg 131.5 17.5 130.5 11.6 130.0 19.6 133.3 17.2 Diastolic, mmHg 79.2 9.8 77.4 8.1 77.2 10.8 81.8 8.9 Smoking Current 6 5.3 1 5.9 2 4.2 3 6.3 Ex-smoker 37 32.7 5 29.4 17 35.4 15 31.3 Never 67 59.3 10 58.8 28 58.3 29 60.4 Missing 3 2.7 1 5.9 1 2.1 1 2.1 Alcohol intake Never 7 6.2 1 5.9 1 2.1 5 10.4 Sometimes 46 40.7 7 41.2 21 43.8 18 37.5 Every week 57 50.4 8 47.1 24 50.0 25 52.1 Missing 3 2.7 1 5.9 2 4.2 0 0.0 Ethnic group White 107 94.7 15 88.2 45 93.8 47 97.9 Black/Asian 3 2.7 0 0.0 2 4.2 1 2.1 Mixed/Other 1 0.9 1 5.9 0 0.0 0 0.0 Missing 2 1.8 1 5.9 1 2.1 0 0.0 Education No formal qualifications 16 14.2 1 5.9 9 18.8 6 12.5 Secondary education 49 43.4 6 35.3 21 43.8 22 45.8 Higher education 46 40.7 9 52.9 17 35.4 20 41.7 Missing 2 1.8 1 5.9 1 2.1 0 0.0 Household size, median (IQR) 2.4 1.2 2.4 1.2 2.3 1.2 2.5 1.3 Adults, mean (SD) 2.1 0.9 2.1 0.8 2.0 0.7 2.2 1.0 Children, mean (SD) 0.3 0.8 0.2 0.6 0.3 0.8 0.4 0.8 Weekly grocery shopping, e.g., spending >£25/trip >Once a week 32 28.3 3 17.7 9 18.8 20 41.7 Once a week 64 56.6 9 52.9 31 64.6 24 50.0 Once a fortnight 6 5.3 2 11.8 2 4.2 2 4.2 Once a month 6 5.3 1 5.9 4 8.3 1 2.1 <Once a month 3 2.7 1 5.9 1 2.1 1 2.1 Missing 2 1.8 1 5.9 1 2.1 0 0.0 Relevant health history Family history 16 14.2 4 23.5 6 12.5 6 12.5 CVD 4 3.5 2 11.8 1 2.1 1 2.1 High blood pressure 27 23.9 4 23.5 14 29.2 9 18.8 Diabetes 0 0.0 0 0.0 0 0.0 0 0.0 AF 4 3.5 2 11.8 1 2.1 1 2.1 CKD 1 0.9 0 0.0 1 2.1 0 0.0 Relevant medications Statins 2 1.8 0 0.0 1 2.1 1 2.1
1 AF, atrial fibrillation; BMI, body mass index; CKD, chronic kidney disease; CVD, cardiovascular disease; IQR, interquartile range.
Change in mean saturated fat intake (%EI) at 3 months (primary outcome) was −0.1% (95% CI −1.8 to 1.7) in the control group, −0.7% (95% CI −1.8 to 0.3) in BS, and −0.9% (95% CI −2.0 to 0.2) in SF (Fig 2, Tables A-B inS4 Appendix). There was no statistically significant difference in either intervention group compared with control (BS versus control = −0.33% [95% CI −2.11, 1.44] p = 0.709; SF versus control = −0.11% [95% CI −1.92, 1.69] p = 0.901; adjusted for GP practice and baseline value) or between intervention groups (S1 Table B).
Graph: Fig 2 Mean (± standard error) changes in saturated fat (% energy intake) from A. dietary recalls (primary outcome) and B. purchases (secondary outcome).SFA, saturated fatty acids.
There were no statistically significant differences between the intervention and control groups in total fat, total daily EI, sugars, dietary fiber (secondary outcomes), or PUFA and MUFA intakes (exploratory outcomes) (Tables A-B inS4 Appendix). Mean total fat intakes (kcal) and daily EIs (kcal) were reduced from baseline to follow-up among the intervention groups: BS = −109.8 kcal (95% CI −214 to −5.6); SF = −79.4 kcal (95% CI −186 to 27.2); and BS = −176.9 kcal (95% CI −393.1 to 39.2); SF = −106.2 kcal (95% CI −327.2 to 114.9), respectively, although these changes were not significant between intervention groups compared with control (Tables A-B in S1 Appendix).
Changes in the intakes of key food groups (%EI) were not statistically significantly different between intervention and control, but there were nonsignificant reductions from baseline to follow-up among the intervention groups (Fig 3, Tables A-B inS4 Appendix): cakes, biscuits, and desserts (BS = −2.6% [95% CI –5.7 to 0.4], SF = 0.5% [95% CI –2.7 to 3.6]); meat (BS = −2.3% [95% CI −4.5 to −0.2], SF = 0.0% [95% CI –2.2 to 2.2]); higher fat cheese (BS = −0.9% [95% CI −1.9 to 0.2]; SF = −1.3% [95% CI −2.3 to −0.2]), higher fat yogurt (BS = 0.2% [95% CI –0.4 to 0.8], SF = −0.8% [95% CI −1.4 to −0.2]), and higher fat spread (BS = −0.8% [95% CI −1.8 to 0.1]; SF = −1.3% [95% CI −2.2 to −0.3]).
Graph: Fig 3 Mean (95% CI) changes in key food groups from A. dietary recalls (%EI) and B. loyalty card data (%TE).EI, energy intake; TE, total energy.
Changes in SFA (%TE) from food purchases at 3 months (secondary outcome) were −0.5% (95% CI −2.3 to 1.2) in the control group, −1.3% (95% CI −2.3 to −0.3) in BS, and −1.5% (95% CI −2.5 to −0.5) in SF (Fig 2, Tables C-D inS4 Appendix), but there were no statistically significant differences between the groups. The adjusted difference in %SFA in the total basket was −0.8% (95% CI −2.5 to 0.9) p = 0.379 between BS versus control; and −0.7% (95% CI −2.4 to 1.0) p = 0.411 between SF versus control. There were no statistically significant differences between groups in total fat, energy density of the basket, sugars, dietary fiber, salt, or basket cost (Tables C-D inS4 Appendix).
Purchases of key food groups (%TE) were not statistically significant between the intervention arms versus control, but there were nonsignificant reductions from baseline to follow-up among the intervention groups, which usually paralleled those observed from the dietary questionnaire data: cakes, biscuits, and desserts (BS = −2.7% [95% CI −6.1 to 0.7]; SF = −3.0% [95% CI −6.4 to 0.4]); meat (BS = −2.1% [95% CI −4.4 to 0.2]; SF = −0.2% [95% CI −2.4 to 2.1]); higher fat cheese (BS = −0.4% [95% CI −1.3 to 0.5]; SF = −0.5% [95% CI −1.4 to 0.5]); and higher fat spread (BS = −0.2% [95% CI −1.4 to 1.1]; SF = −0.7% [95% CI −2.0 to 0.5]) (Fig 3, Tables C-D inS4 Appendix).
Changes in blood lipids were not statistically significantly different between intervention and control. In the BS group, there was a nonsignificant reduction from baseline to follow-up in LDL (−0.39 mmol/L [95% CI −0.59 to −0.19]), and in the SF group (−0.14 mmol/L [95% CI −0.34 to 0.07]) (Table 2, Table E inS4 Appendix). Changes in body weight and blood pressure were not significantly different between groups either, but there were small nonsignificant reductions in weight from baseline to follow-up in both intervention groups (BS = −1.1% [95% CI −1.9 to −0.3]; SF = −0.8% [95% CI −1.6 to 0.0]).
Graph
Table 2 Changes in clinical outcomes: Secondary and exploratory outcomes by group allocation.
Change from baseline within group Between-group differences adjusted for baseline and practice Control ( BS ( BS plus SF ( BS versus control BS+SF versus control BS+SF versus BS Secondary Outcomes Mean 95% CI Mean 95% CI Mean 95% CI Mean 95% CI Mean 95% CI Mean 95% CI LDL cholesterol (mmol/L) −0.14 (−0.48, 0.19) −0.39 (−0.59, −0.19) −0.14 (−0.34, 0.07) −0.15 (−0.47, 0.16) 0.338 0.04 (−0.28, 0.36) 0.790 0.2 (−0.03, 0.43) 0.095 HDL cholesterol (mmol/L) 0.08 (−0.03, 0.19) −0.01 (−0.08, 0.05) −0.02 (−0.09, 0.04) −0.11 (−0.24, 0.01) 0.081 −0.13 (−0.26, 0.00) 0.047 −0.02 (−0.11, 0.07) 0.713 Total cholesterol (mmol/L) −0.13 (−0.46, 0.21) −0.46 (−0.66, −0.25) −0.14 (−0.35, 0.06) −0.3 (−0.62, 0.02) 0.069 −0.02 (−0.34, 0.30) 0.910 0.28 (0.04, 0.51) 0.02 Triglycerides (mmol/L) −0.14 (−0.54, 0.26) −0.14 (−0.38, 0.11) −0.01 (−0.25, 0.24) 0.04 (−0.37, 0.46) 0.836 0.27 (−0.15, 0.69) 0.211 0.22 (−0.09, 0.53) 0.154 Non−HDL cholesterol (mmol/L) −0.21 (−0.56, 0.14) −0.44 (−0.65, −0.24) −0.12 (−0.33, 0.09) −0.16 (−0.51, 0.19) 0.362 0.15 (−0.20, 0.50) 0.393 0.31 (0.06, 0.56) 0.016 Total cholesterol/HDL ratio −0.15 (−0.59, 0.29) −0.34 (−0.60, −0.07) 0.02 (−0.24, 0.29) −0.13 (−0.64, 0.37) 0.601 0.25 (−0.26, 0.76) 0.335 0.38 (0.01, 0.75) 0.042 Nonefficacy Outcomes Systolic blood pressure (mmHg) 0.5 (−6.3, 7.4) 1.3 (−2.8, 5.4) 1.2 (−3.0, 5.3) 0.58 (−7.01, 8.18) 0.879 1.44 (−6.23, 9.11) 0.710 0.86 (−4.68, 6.40) 0.759 Diastolic blood pressure (mmHg) 1.2 (−2.7, 5.2) −0.3 (−2.7, 2.0) −0.5 (−2.9, 1.9) −1.42 (−5.80, 2.97) 0.523 −0.01 (−4.50, 4.48) 0.997 1.41 (−1.87, 4.69) 0.397 Weight (kg) −0.2 (−1.5, 1.1) −1.1 (−1.9, −0.3) −0.8 (−1.6, 0.0) −1.00 (−2.52, 0.53) 0.197 −0.57 (−2.11, 0.98) 0.468 0.43 (−0.69, 1.55) 0.449
2 BS, brief support; GP, general practioner; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SF, brief support plus shopping feedback.
There was no evidence of a significant interaction between trial arm and education status (secondary education only versus more advanced education) on %SFA intake, %SFA purchases, or LDL-C (Fig 4, Table F inS4 Appendix). Among those allocated to BS group but not SF group, there was a greater reduction in SFA consumption and purchase in participants with lower levels of education, but that was not statistically significant to control (Fig 4).
Graph: Fig 4 Mean (95% CI) changes in saturated fat from A. dietary recalls (%EI) and loyalty card data (%TE) and B. LDL cholesterol (mmol/L) by group and education status.BS, brief support; EI, energy intake; LDL, low-density lipoprotein; SF, brief support plus shopping feedback; SFA, saturated fatty acids; TE, total energy.
None of the sensitivity analyses changed the overall pattern of results but in most cases, resulted in slightly larger absolute differences between the intervention groups and control group (Table G inS4 Appendix).
Of 4,766 people invited to take part in the study, 181 (4%) responded to the invitation, from which 143 participants (3%) fulfilled some of the eligibility criteria (e.g., were customers of the participating supermarket) and consented and agreed to be screened for full eligibility. Of those, 30 (21%) were ineligible, mostly because LDL cholesterol was <3 mmol/L at the time of recruitment, giving 2.4% of the original sample of invited participants who were then randomized. Of these, 94% were followed up after 3 months.
There was an average of 37 days (SD 22) between the baseline visit with researchers and the brief advice appointment with the HCP. The BS sessions delivered by the HCP were audio-recorded with an average duration of 10 minutes (range 3 minutes to 30 minutes). Out of 19 possible behavioral elements included in the training, an average of 10 (range 3–19) were evident in the recordings. Two of the elements that were missed the most were asking participants if they had already identified a specific food to change and the take-home message in which the HCP provided an overall overview of the main points discussed.
The SF group received a mean of 3.6 shopping reports. Each shopping report included 5 potential swaps. Approximately 41% of lower SFA swaps offered were dairy products (e.g., cheese, yogurt, milk/cream, spread/butter); 21% cakes, biscuits, and desserts; 17% meat (e.g. beef, pork, processed meat); 7% ready meals (e.g., pizza, pies); and 13% from other categories (e.g., salty snacks, oils, bread, cereal). One in 4 suggested swaps appeared in the subsequent purchase record during the intervention period. These "accepted swaps" came from cheese, yogurt, milk/cream or spread/butter (58%); cakes, biscuits, and desserts (15%); meat (13%); salty snacks (2%); and ready meals (2%) (Table H inS4 Appendix).
Overall, participants reported that the HCP intervention session and self-help materials were helpful, with mean scores of 3.9 among BS and 3.7 among SF (on a scale 1–5). Participants in the SF group considered the shopping report was moderately helpful with a score of 3.5, and 43% reported using the shopping report "almost always" or "most of the time" when shopping. A higher proportion of participants in the intervention groups reported being "very/somewhat confident" that they knew the major sources of SFA in their diets after the intervention. A higher proportion of participants in all groups were trying to reduce SFA in their diets at follow-up than at baseline (Table H inS4 Appendix).
Among people identified as having modestly raised LDL-C, there was no strong evidence that a brief behaviorally informed appointment with a HCP with or without additional personalized shopping feedback and swap suggestions for the saturated fat content of food purchases reduced SFA consumption, SFA food purchases, or LDL-C relative to a control group. However, the reductions in SFA and LDL cholesterol in the intervention groups were not significant but larger than those in the control with no formal intervention. The intervention was feasible, acceptable, and potentially scalable.
This pragmatic study did not detect a reduction in SFA or LDL cholesterol of a magnitude to imply that this intervention is an effective alternative to lipid-lowering therapy for individuals with raised LDL. Explanatory trials, which provided specific foods to replace higher SFA products, together with intensive tailored counseling, have shown greater reductions in SFA (approximately 4%–5%) with small reductions in LDL cholesterol of approximately 0.2 mmol/L [[
Although there is limited clinical benefit to individuals of very small reductions in SFA, there could be important population-level health gains. Systematic reviews of trials of interventions to reduce SFA intake compared with usual diets showed interventions reduced LDL by −0.19 mmol/L (−0.33, −0.05) yet decreased the incidence of nonfatal CVD events by 17% [[
A strength of this study is the randomized controlled trial (RCT) design and high follow-up rate (94%), which reduces the effect of confounding and provides high internal validity. The average monthly spend across groups and over time was largely unchanged, suggesting that the intervention did not disrupt usual shopping patterns. Our primary outcome was based on a dietary recall method, which is subject to misreporting, and included only 2 days of reporting at baseline and follow-up, but potential bias is reduced by the comparison with a control group. Total EI data measures are consistent with the observed weight changes, and there was good agreement in the measured change in SFA and key food groups in each group between the dietary recall and the household food purchase data. A previous study also showed strong correlations approximately 0.8 between total energy and fat between dietary recalls and food purchases, which suggest that the use of purchasing data is feasible, inexpensive, and accurate for nutritional research in populations in which most food comes from supermarkets [[
The principal limitation of the study is the sample size, which lacked power to detect smaller effect sizes. The participants randomized were a very small proportion of those eligible and may have been biased to those with higher levels of concern about their diet. It is possible that participants in the control group could have been prompted to reduce their SFA upon receiving their blood test results and the notice of a future check 3 months later, which reduced the chance of detecting a difference between groups. Only 2 participants were taking lipid-lowering medications, and this may also imply a motivated group already taking action, which could limit the opportunity for further change. Our population included a higher proportion of middle/older age participants, reflecting the population with dyslipidaemia [[
The shopping feedback used a novel computerized algorithm to process information from loyalty cards and provide tailored dietary advice in real-time. By drawing on the power of data already collected by grocery stores, we could deliver personalized advice, which would otherwise require specialist practitioners, usually dieticians, considerable time to analyze and would strain healthcare resources. There was no difference observed between the groups receiving brief advice only and those also receiving personalized shopping reports. For this highly selected population, it is possible that brief advice is enough to change food purchasing and consumption, and we do not know the effect of tailored shopping advice alone. Only 3 studies have previously observed absolute reductions in SFA intake with interventions focused on food purchasing. A study of tailored education (e.g., frequently mailed tailored shopping lists, recipes, and healthier alternatives) based on previous purchases showed a reduction of −1.4% in SFA in all food purchases at 6 months, but this was not significantly greater than the control group [[
Importantly saturated fat intake and %SFA in total purchases declined in both intervention groups for the food categories that contribute the most to SFA intakes in the UK, and the changes were congruent with the emphasis of the advice provided. The written information provided in the brief advice group focused on meat as well as dairy intake and purchases and intake of these foods, especially meat, declined in the BS group. In contrast, most swaps offered in the shopping reports and accepted in the SF group were for dairy products. The slightly larger reductions in LDL cholesterol in the BS compared with the SF group are consistent with recent epidemiological evidence on the effects of individual fatty acids found in different concentrations in meat and dairy products [[
In qualitative questionnaires, participants highly valued the shopping reports and reported them to be useful for self-monitoring. Given the relative ease and low cost of providing this information at scale, it warrants further investigation as a public health intervention for people seeking to reduce the SFA content of the diet. A similar approach could potentially be adopted for other nutrients of concern, e.g., salt or free sugars, by retail partners who may wish to offer this type of support to their customers. Only a few studies have used information on household food purchases from loyalty cards, usually to monitor the effectiveness of interventions or to provide personalized dietary advice [[
In conclusion, our trial showed nonsignificant reductions in SFA intake, the SFA content of household food purchases, and LDL-C. The small changes we observed are consistent with other individual-level behavioral interventions to reduce SFA, but the study was underpowered to detect all but large improvements. With further enhancement of the intervention based on participants' feedback, the good evidence of feasibility and acceptability of using grocery loyalty card data offers the potential to develop an automated, low-cost, and scalable intervention that could reach and benefit large numbers of people to deliver population-level impacts, which may improve public health.
S1 Appendix. Study protocol.
(DOCX)
S2 Appendix. List of inclusion and exclusion criteria.
(DOCX)
S3 Appendix. Qualitative questionnaire.
(DOCX)
S4 Appendix. Supplementary tables.
(DOCX)
S5 Appendix. CONSORT checklist.
CONSORT, Consolidated Standards of Reporting Trials.
(DOC)
We would like to thank Mei-Man Lee (medical statistician) for providing input into the statistical plan and the sample size calculation for this trial. We would like to thank the members of the public who helped reviewing materials at the initial stages of the grant application and during the intervention development. We also thank the 4 practices that participated in the study and the practice staff (practice managers, HCP, GPs, receptionists) involved in the recruitment and intervention delivery. We finally thank all the participants that were willing to take part in the study.
The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.
• BMI
- body mass index
• BS
- brief support
• CVD
- cardiovascular disease
• EI
- energy intake
• GP
- general practitioner
• HCP
- healthcare professional
• LDL-C
- low-density lipoprotein cholesterol
• MUFA
- monounsaturated fatty acids
• NHS
- National Health System
• PUFA
- polyunsaturated fatty acids
• RCT
- randomized controlled trial
• SF
- shopping feedback
• SFA
- saturated fatty acids
• TE
- total energy
By Carmen Piernas; Paul Aveyard; Charlotte Lee; Melina Tsiountsioura; Michaela Noreik; Nerys M. Astbury; Jason Oke; Claire Madigan and Susan A. Jebb
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