Evaluation of an intervention to provide brief support and personalized feedback on food shopping to reduce saturated fat intake (PC-SHOP): A randomized controlled trial

Autor: Michaela Noreik, Claire D Madigan, Nerys M. Astbury, Charlotte Lee, Jason Oke, Paul Aveyard, Susan A. Jebb, Carmen Piernas, Melina Tsiountsioura
Jazyk: angličtina
Rok vydání: 2020
Předmět:
0301 basic medicine
Male
Saturated fat
Psychological intervention
Cardiovascular Medicine
Biochemistry
law.invention
Body Mass Index
Fats
0302 clinical medicine
Medical Conditions
Randomized controlled trial
law
Animal Products
Medicine and Health Sciences
Medicine
030212 general & internal medicine
Response rate (survey)
education.field_of_study
Agriculture
General Medicine
Middle Aged
Lipids
Cholesterol
Cardiovascular Diseases
Female
Research Article
Adult
medicine.medical_specialty
Meat
Lipoproteins
Population
Cardiology
Primary care
Feedback
03 medical and health sciences
Intervention (counseling)
Humans
education
Primary Care
Nutrition
030109 nutrition & dietetics
business.industry
Biology and Life Sciences
Proteins
Diet
Health Care
Food
Physical therapy
business
Energy Intake
Body mass index
Zdroj: PLoS Medicine
PLoS Medicine, Vol 17, Iss 11, p e1003385 (2020)
ISSN: 1549-1676
1549-1277
Popis: 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.
Databáze: OpenAIRE
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