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Final Report

West London Food Waste Prevention

Campaign Evaluation Report

ISBN: 978-1-84405-468-8 Project code: CFP104-030 Research date: September 2012 – July 2013 Date: September 2013

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Written by: Tom Quested (WRAP), Robert Ingle (support to WRAP from SKM Enviros)

Front cover photography: WLWA Cookery Demonstration

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West London Food Waste Prevention Campaign Evaluation Report 1

Executive summary

Background Food waste prevention is a key priority for WRAP and the Governments of the UK. WRAP has run a consumer food waste prevention programme and consumer facing campaign, Love Food Hate Waste (LFHW1), since 2007. LFHW operates across the UK, communicating directly to consumers to raise awareness of the benefits of reducing food waste, and to provide a wide range of tools and advice, primarily through PR, the website and social media. LFHW also enables a wide range of partner organisations to help consumers reduce food waste. WRAP also undertakes technical activity with the food industry, to change the retail environment (e.g. change products, packaging, labelling and the way food is sold) to help consumers waste less. In 2009, WRAP published Household Food and Drink Waste in the UK2. This found that around 8.3 million tonnes of food and drink was thrown away in 2007 in the UK (22% of all the food and drink purchased) and 5.3 million tonnes of this could have been consumed (i.e. was avoidable). WRAP announced a reduction in total household food and drink waste of 1.1 million tonnes in November 2011; avoidable food and drink waste reduced by 950,000 tonnes. A range of factors, such as the work of WRAP and its partners (including the LFHW campaign), increasing food prices and difficult economic conditions will have played a role in bringing about this reduction in food waste, but determining the extent to which each of the various factors have played a role is extremely challenging. Research has been undertaken to understand the contribution of these elements3. The Greater London Authority (GLA) and WRAP worked in partnership to deliver the Recycle for London programme funded by the London Waste and Recycling Board (LWARB). Between October 2012 and March 2013 Recycle for London delivered a pan-London LFHW campaign and supported local borough activity. The pan-London campaign included radio, digital and print advertising along with supporting PR activity and events. One of the local campaigns was carried out across the six boroughs of the West London Waste Authority area. The campaign consisted of a variety of approaches including community engagement (such as cookery classes and a volunteer network), PR and advertising. This campaign across West London provided an opportunity to understand the impact of LFHW campaigns in reducing food waste. Funding was available to monitor changes in food waste levels either side of the campaign. Given the intensity and geographical bounding of the campaign, it was likely that, if there were a food-waste reduction, it could be detected via an affordable piece of research. Research This study investigates and quantifies the impact of the LFHW campaign in West London that ran from autumn 2012 to spring 2013. The research described in this report has two principal elements:

1 www.lovefoodhatewaste.com

2 WRAP (2009): Household Food and Drink Waste in the UK. Available at: http://www.wrap.org.uk/sites/files/wrap/Household%20food%20and%20drink%20waste%20in%20the%20UK%20-%20report.pdf

3 The research report will be published Winter ’13 (CFP101-008).

http://www.lovefoodhatewaste.com/

http://www.wrap.org.uk/sites/files/wrap/Household%20food%20and%20drink%20waste%20in%20the%20UK%20-%20report.pdf

http://www.wrap.org.uk/sites/files/wrap/Household%20food%20and%20drink%20waste%20in%20the%20UK%20-%20report.pdf


Measurement of changes in the amount of food waste generated by West London households using waste compositional analysis (with informed consent of the participating households); and

Investigation into changes in attitudes, awareness and behaviour relating to household food waste using a face-to-face quantitative survey (household interviews).

These two elements of fieldwork were performed on the same households both before and after the campaign. This allowed the results to be linked, ensuring a greater understanding of any impacts the campaign made within the targeted area. Results The average amount of food waste generated within the sample decreased by 15% (±14%) from 2.60 kg / household / week pre-campaign to 2.20 kg / household / week post-campaign (Table ES1). This reduction is statistically significant at the 95% confidence level. The majority of this is the result of decreases in food waste in the general (residual) waste stream; levels in the food-waste collections were similar before and after the campaign.

Table ES1: Average amount of food waste before and after the campaign split by disposal route

Amount of food waste (kg / hh / week) Significance of change Pre Post Difference %

Residual 1.22 0.91 –0.31 -26% >95%

Food waste collections

1.37 1.28 –0.09 -6% not sig.

Total 2.60 2.20 –0.40 -15% >95%

Both avoidable and unavoidable food waste reduced, with avoidable food waste reducing by 0.17 kg / hh / week (14%) and unavoidable food waste reducing by 0.27 kg / hh / week (24%). This decrease in food waste was accompanied by a shift towards behaviours that are associated with lower levels of food waste, such as planning meals, making shopping lists and wrapping items (e.g. cheese) appropriately to optimise their shelf life. The reduction in unavoidable food waste is consistent with information from the survey, which showed an increase in the number of people using leftovers as a meal or as part of another meal. Less food being prepared from scratch, as a result of not wasting as much of the food that is cooked, results in less unavoidable preparation waste. In addition, other factors involved could include changes in cooking practices (less home cooking), altered purchasing patterns (change to purchasing food that is not prepared at home) and potentially seasonality (less unavoidable waste produced from foods purchased in May than October, e.g. more root vegetables are purchased during autumn and winter than spring and summer). A group of people within the sample reported that they were strongly influenced by the campaign and other food-waste messaging. Specifically, 14% of households interviewed after the campaign had seen something recently about food waste and said they were doing something different as a result. The waste compositional analysis shows that this group reduced their total food waste by 1.1 kg / hh / week (a 35% reduction); a large part of that reduction was associated with avoidable food waste: a 0.7 kg / hh / week or 43% reduction.


Although based on only 62 households (out of the total matched sample of 452), these reductions are significant at the 95% confidence level due to the magnitude of the reductions. This group contributes around half of the total reduction in food waste in the sample. Alongside this research, WRAP runs a regular food waste prevention consumer survey across Great Britain. Data were available for Great Britain, London and West London. This did not show any significant changes in stated behaviour in key activities related to food waste. However, the sample size for West London was small (less than 200), and therefore only large shifts would have been detectable. Limitations This study does not cover food and drink waste that is disposed of down the drain, home composted or fed to animals. The effect of the campaign on these disposal routes cannot therefore be quantified and the potential diversion of food waste to them cannot be ruled out, although it should be stressed that the aim and messaging of the campaign was around food waste prevention, and the benefits associated with this (e.g. financial savings), not about avoiding food waste going to landfill. These disposal routes were not included as they represent a minority of total arisings and are more difficult to directly measure than waste collected by local authorities. Although asking a sample of people to record information in a kitchen diary is feasible, it would have increased the project budget considerably. The study did not have a control group. Therefore, alternative data sources were investigated to assess the impact of other influences on food waste (Appendix B). Food-purchasing data suggested that the positive changes in food-waste levels seen were not strongly influenced by seasonal fluctuations in food purchases. Furthermore, econometric modelling indicated that the relatively minor changes in food prices and income levels that occurred over this time period were not responsible for changes in food waste levels. However, a proportion of the reduction could be related to the research effect, whereby the act of being interviewed has an influence on behaviours and waste levels. Therefore, the results presented below should be seen as an upper limit on the impact of this campaign. It is also difficult to assign the measured reduction in food waste that is attributable to a) national campaign activity, b) the pan-London campaign, and c) West-London-specific activities. This is because activity was on-going at all three levels in West London at the time of the research. Some of the activity would have used similar messages and imagery, thus working together to elicit reductions in food waste. In addition, non-LFHW messages would have been apparent in West London during the campaign period. Given the above, recommendations are made in Appendix B regarding designs for future research. Conclusions These results indicate that the campaign was effective, raising awareness about the issue of food waste and successfully encouraging people to change key behaviours and reduce food waste. If all the changes seen were the result of the campaign (see limitations), the reduction in the amount of avoidable food waste is equivalent to 5,250 tonnes per annum for households in West London. Purchasing the food that is eventually wasted would cost West Londoners approximately £14 million and avoiding it becoming waste would save greenhouse-gas emissions equivalent to


20,000 tonnes of CO2e. Assuming a total disposal cost of £106.50 per tonne4 the reduction in avoidable food waste would save the boroughs of West London £559,000 per annum in disposal costs (including gate fees and landfill tax). If the reduction in unavoidable food waste is included, the total saving in disposal costs to the boroughs of West London is estimated to be up to £1.3 million per annum. The costs associated with delivering the campaign were around £170,000, which would mean that for every £1 invested, West London Boroughs saved up to £85. If the 14% reduction in avoidable food waste was scaled up to the whole of London6 for a year we would see a reduction of 29,400 tonnes of avoidable food waste. This would see a £79 million cost saving to residents. If the reductions in total food waste were scaled up to the whole of London for a year this would equate to around 68,000 tonnes, resulting in cost savings to Local Authorities from avoided disposal costs of up to £7.3 million.

4 It should be noted that the disposal charge during the period of the campaign was £93 a tonne. The current disposal charge is £106.50 and has been used for the purposes of this report.

5 Based on reductions in total food waste.

6 3.33 million households (DCLG); the scaling up of the savings is indicative only; impact is likely to vary by population characteristics and the sample for this research was designed to represent West London not the population of London as a whole.


Contents

1.0 Overview, aims and justification for this research ....................................... 8 2.0 Details of the Love Food Hate Waste campaign in London ........................... 9

2.1 Background ............................................................................................... 9 2.2 London-wide activity .................................................................................. 9 2.3 Campaign in the West London boroughs .................................................... 11

3.0 Methodology ............................................................................................... 13 3.1 Methods for the household interviews ........................................................ 13 3.2 Methods for waste compositional analysis .................................................. 15

3.2.1 Waste streams sampled .................................................................. 15 3.2.2 Material classification ..................................................................... 16

3.3 Details of sampling ................................................................................... 16 3.4 Sample size, confidence levels and weighting ............................................. 19

3.4.1 Weighting of cases for the household interviews ............................... 20 3.4.2 Weighting of cases for the waste compositional analysis.................... 21

4.0 Results ........................................................................................................ 22 4.1 Waste compositional analysis: changes in the amount of food waste ............ 22 4.2 Results from the household interviews ....................................................... 25

4.2.1 Meal planning ................................................................................ 26 4.2.2 Checking food stocks ...................................................................... 27 4.2.3 List making .................................................................................... 28 4.2.4 Use of a freezer ............................................................................. 28 4.2.5 Storage of open cheese and meat ................................................... 29 4.2.6 Use of the fridge to use fruit or vegetables ....................................... 30 4.2.7 Use of left overs ............................................................................ 30 4.2.8 Cooking the right amount ............................................................... 32 4.2.9 Use of date labels .......................................................................... 33 4.2.10 Self-reported waste levels ............................................................... 34

4.3 Results from WRAP’s regular household food waste consumer survey ........... 36 5.0 Discussion of results ................................................................................... 37 6.0 Potential cost and environmental savings .................................................. 40 7.0 Conclusions and Recommendations ........................................................... 41 Appendix A: Peer Review Statement .................................................................... 42 Appendix B: Discussion of Factors that may Influence Results ............................ 43 Appendix C: Pre-Campaign Questionnaire ........................................................... 48 Appendix D: Post-Campaign Questionnaire ......................................................... 55 Appendix E: Waste Composition Sort Sheet ......................................................... 63


Figures

Figure 1: Venn-diagram representation of samples for a) household interviews and b) waste compositional analysis .................................................................................................. 18 Figure 2: Summary of Behavioural Scorecard ................................................................ 26 Figure 3: Responses to interview question: To what extent do you decide what you are going to eat for main meals in advance? (only one response allowed). ............................. 26 Figure 4: Responses to interview question: Think about the last time you did a main grocery shop. Before a particular shop did you check what you already had at home for any of the following? (percentage shown is those answering yes). ................................................... 27 Figure 5: Responses to interview question: ‘Still thinking about the last time you did a main grocery shop do any of these describe what you did before that shopping trip?’ (Multiple responses are allowed) ................................................................................................. 28 Figure 6: Responses to interview question: Excluding food that was frozen when you bought it, which of the following items have you put into the freezer in the past week? ..... 28 Figure 7: Responses to interview question: Think about the last time you opened an item of cheese. How did you store these after opening?’ (Multiple responses allowed)................... 29 Figure 8: Responses to interview question: Think about the last time you opened an item of sliced meat. How did you store these after opening?’ (Multiple responses allowed) ........... 29 Figure 9: Responses to interview question: Think about the last time you went shopping and purchased fresh apples or carrots or potatoes. When you returned home, where did you store it?’ ...................................................................................................................... 30 Figure 10: Responses to interview question: Thinking about the last time you had leftovers or made more food than you needed. What happened to those leftovers? (Multiple responses allowed). ..................................................................................................................... 31 Figure 11: Responses to interview question: Think back to the last time you cooked a meal based on rice. At the end of the meal did you have any uneaten rice? (Only single response allowed). ..................................................................................................................... 32 Figure 12: Responses to interview question: Think back to the last time you cooked a meal based on pasta. At the end of the meal did you have any uneaten pasta?’ (Only single response allowed) ........................................................................................................ 32 Figure 13: Responses to interview question: Over the past week have you thrown any of the following away because they have gone past the date on the packaging?.................... 33 Figure 14: Responses to interview question: Thinking about the different types of food discussed in the previous question, how much uneaten food, overall, would you say you generally end up throwing away? .................................................................................. 34 Figure 15: Responses to interview question: Over the LAST WEEK, how much of the following foods have you thrown away (in a compost bin, ordinary bin, council collection, down the sink or fed to pets etc.)? Scored on a scale of 0 to 5. * indicates statistically significant difference at 95% confidence level. ................................................................ 35 Figure 16: Consumer Prices Index (CPI) for food and all items during the time-period of the campaign (Indexed, October 2012 = 100) ...................................................................... 44 Figure 17 : Average residual for each calendar month showing the seasonal variation taking into account long-term trends ....................................................................................... 46


Tables

Table 1: Key themes for the London wide campaign included: .......................................... 9 Table 2: Food waste collection type for boroughs in West London ................................... 15 Table 3: Sample sizes for difference elements of the research ........................................ 18 Table 4: Effect of weighting on average behavioural score (out of a possible score of ten) 20 Table 5: Effect of weighting on total amount of household food waste (kg per household per week) .......................................................................................................................... 21 Table 6: Average food waste per household per week in West London by disposal route. .. 22 Table 7: Food waste by avoidability .............................................................................. 23 Table 8: Food waste by food category .......................................................................... 23 Table 9: Average arisings of food waste from households who were aware of the food-waste messaging and said they weredoing something differently as a result...................... 25 Table 10: Headline results from WRAP regular food waste consumer survey .................... 36

Glossary

Defra – Department for Food Environment and Rural Affairs

GLA – Greater London Authority

LFHW – Love Food Hate Waste

LWaRB – London Waste and Recycling Board

PR – Public Relations

RfL – Recycle for London

ONS – Office of National Statistics

WLWA – West London Waste Authority (which covers the London boroughs of Harrow, Hounslow, Richmond-upon-Thames, Brent, Ealing and Hillingdon)

WRAP – Waste & Resources Action Programme

Acknowledgements

The authors of this report gratefully acknowledge the work of the contractors who undertook the fieldwork for this project: Exodus Research Ltd and Waste Intelligence Ltd. In addition, we would like to thank the boroughs who gave permission for fieldwork to take place, and Sarah Ellis from the West London Waste Authority for facilitating this process. Andrew Brigden and Erik Britton from Fathom Consulting are thanked for their econometric modelling that fed into the section of the appendices on the influence of economic factors on food waste. Also, thanks to Karen Stark from Defra for provision of the monthly data from the Family Food Survey. We would also like to thank colleagues at WRAP for useful comments on the report: Ella Clarke, Faye Gracey, Sophie Easteal, Emma Marsh and Andrew Parry. The peer reviewer – Robin Curry (SRI Consulting) – is also thanked for his useful and constructive comments and input. His statement is given in Appendix A.


1.0 Overview, aims and justification for this research Food waste prevention is a key priority for WRAP and its funders (the Governments of the UK). WRAP has run a consumer food waste prevention programme, and consumer facing campaign, Love Food Hate Waste (LFHW7), since 2007. LFHW operates in all four nations of the UK, communicating directly to consumers to raise awareness of the benefits of reducing food waste, and providing a wide range of tools and advice, primarily through PR, the website and social media. LFHW also enables a wide range of partners (for example, retailers, food brands and other businesses, local authorities, community groups) to help consumers reduce food waste by making insights, templates, toolkits and guidance available. WRAP also undertakes technical activity with the food industry, to change the retail environment (e.g. change products, packaging, labelling and the way food is sold) to help consumers waste less. In 2009, WRAP published Household Food and Drink Waste in the UK8. This found that around 8.3 million tonnes of food and drink was thrown away in 2007 in the UK (22% of all the food and drink purchased) and 5.3 million tonnes of this could have been consumed. WRAP announced a reduction in total household food and drink waste of 1.1 million tonnes in November 2011; avoidable food and drink waste reduced by 950,000 tonnes. A range of factors, such as the work of WRAP and its partners (including the LFHW campaign), increasing food prices and difficult economic conditions will have played a role in bringing about this reduction in food waste, but determining the extent to which each of the various factors have played a role is extremely challenging. Research has been undertaken to understand the contribution of these elements. The aim of this research is to investigate and quantify the outcomes of the LFHW campaign in West London that ran from autumn 2012 to spring 2013, as described in section 2.0. West London was selected for this research due to the level of internal resource (both staff and funding) that they could dedicate to the campaign project; this combined with Recycle for London support meant that there was considerable activity delivered across the area, which was required for the evaluation. There was also willingness from the boroughs of West London for this evaluation research to progress9. The research has two principal elements:

Measurement of any changes in the amount of food waste generated by West London households using waste compositional analysis; and

Investigation into changes in attitudes, awareness or behaviour relating to household food waste using a quantitative survey (household interviews).

These two elements of fieldwork were performed on the same households before and after the campaign, allowing the results to be linked, ensuring a greater understanding of any impacts the campaign has made within the targeted area. The methodology used is described in section 3.0, with the results in section 4.0, discussion of these results in section 5.0 and the cost and environmental saving are in section 6.0. Further discussion of factors that may influence the results in Appendix B, with the pre- and post-campaign questionnaires included in Appendix C and D. Appendix E includes the post campaign ‘sort sheet’ used to conduct the household interviews.

7 www.lovefoodhatewaste.com

8 WRAP (2009): Household Food and Drink Waste in the UK


http://www.lovefoodhatewaste.com/


2.0 Details of the Love Food Hate Waste campaign in London 2.1 Background In 2012 / 13 Recycle for London (RfL) developed and ran a London-wide LFHW campaign, in response to the volume of food wasted by London households and the costs associated with its disposal. Activity was delivered on the following three levels, each aimed at contributing to the impact of the campaign in London:

National activity – delivered in line with the LFHW national campaign calendar10 (delivered by Waste & Resources Action Programme (WRAP)).

London-wide – awareness raising activity in line with key bursts of national activity (delivered by Greater London Authority (GLA)) – see section 2.2.

Local / Community engagement – communications activity at a borough level and community engagement activity supported by the volunteering sector (delivered by West London Waste Authority (WLWA) and WRAP) – see section 2.3.

2.2 London-wide activity RfL delivered London-wide activity at key points, in line with the national LFHW campaign calendar. London-wide activity consisted of above-the-line advertising11 supported by public relations (PR), digital activity and stakeholder engagement. Table 1 shows the key themes of the campaign.

Table 1: Key themes for the London-wide campaign included:

Date Calendar link

October 2012 Harvest and water

November 2012 European Week of Waste Reduction

December 2012 Christmas

January 2013 New Year

February 2013 Valentine’s Day

March 2013 Lent/Easter and Fresher for Longer12

Based on national research and creative (designs), the core message of the London LFHW campaign was ‘You could save up to £50 per month by throwing away less food.’ Activities during the campaign period included:

Radio advertising – a 30 second radio advert ran on 8 London radio stations for 2 weeks in November/December 2012 and reached 60% of Londoners aged 25-44 (2.6 million people), who each heard the advert an average of 7 times.

Digital Adverts – the digital advertising campaign included banner adverts on a range of websites, and adverts linked to search terms on Google. Both methods of digital

10 http://www.lovefoodhatewaste.com/partners

11 Above-the-line is a type of advertising using traditional media such as television, radio and print.

12 http://england.lovefoodhatewaste.com/blog/2013/03/fresher-longer-come-lets-stay-together

http://www.lovefoodhatewaste.com/partners

http://england.lovefoodhatewaste.com/blog/2013/03/fresher-longer-come-lets-stay-together


advertising were linked to lovefoodhatewaste.com to direct people to the website. In both cases, the adverts were targeted geographically using IP addresses, ensuring that Londoners were reached.

London Underground Advertising – LFHW adverts ran on 465 poster sites across the London underground networks for one month (4th to 31st January 2013). The posters reached 23% of Londoners (1.85 million people) who each had an average of 32 opportunities to see the posters.

One quarter-page advert was placed in the Metro newspaper on 3rd January 2013, reaching an estimated 17% of Londoners (1.42 million people).

Digital adverts appeared on the Transport for London on-line Journey Planner for one month.

Social Media – RfL actively used social media channels, such as Facebook and Twitter, to engage directly with London residents about LFHW. This included promoting key messages in line with national campaign activity, and promoting London events. Between October 2012 and March 2013 there were a total of 1,122 updates via RfL social media. The number of people reached through Facebook during this period was 12,483 and 648 tweets generated 1.39 million impressions and had a reach of 555,648. In addition to London-specific social-media activity, national social-media activity would have also contributed to these figures but it is not possible to break them down for London.

Lovefoodhatewaste.com – the national website included a section dedicated to the London campaign, which was promoted as a banner on the home page. During the campaign period there were 89,199 visits to the LFHW website from Londoners (based on IP address locations) of which 73% were new visitors to the site.

PR – Press releases were used to support each of the key bursts of activity. Unfortunately there was little pick up in the printed media, although ITV news covered the London LFHW campaign twice in January 2013.

Events – RfL ran events to raise awareness of the LFHW campaign including the “Food Waste Challenge”, working with Londoners to challenge them to reduce the food that they throw away. Other events were supported by the RfL team, including the Alternative Valentines Banquet and the “Feaster” banquet in partnership with Food Cycle. Both events involved meals being made from surplus food to highlight the issue of food waste. These events reached a total of 226 people including direct engagement with 52 Londoners through the food waste challenge, 80 people attended the Valentines Banquet and 90 people attended the Feaster Event. The reach of the food waste challenges was extended to 131,402 people through social media (#FoodWasteChallenge).

Food Waste Champions – London-wide recruitment and training of 2,397 “Food Waste Champions” (416 trained in West London) to cascade messages to local communities about how to reduce the amount of food thrown away and save money. Once trained, Food Waste Champions are encouraged as a minimum to pass messages on to friends and family and to identify opportunities for reaching wider audiences. It is estimated13 that the Food Waste Champions cascaded the messages to a further 39,795 Londoners.

Internal communications – a range of internal communications were delivered within the GLA and public organisations including the London Fire Brigade and The Metropolitan Police. Within the GLA, 750 employees received an internal newsletter.

13 Estimate was made using WRAP’s evaluation approach described here: http://www.wrap.org.uk/content/evaluating-impact-wrap%E2%80%99s-cascade-training-programme-england-201112

http://www.wrap.org.uk/content/evaluating-impact-wrap%E2%80%99s-cascade-training-programme-england-201112

http://www.wrap.org.uk/content/evaluating-impact-wrap%E2%80%99s-cascade-training-programme-england-201112


2.3 Campaign in the West London boroughs RfL also provided the WLWA with funding and advisory support to deliver LFHW activity across the six constituent boroughs. In addition to funding from RfL, WLWA also contributed significant internal resource to the delivery LFHW. In addition to direct funding support from RfL, West London also benefited from London-wide Volunteer coordinator activity, which recruited and trained Food Waste Champions within communities across London and encouraged them to cascade messages about how to reduce food waste and save money within local communities. Activity in West London focused on raising awareness of the issue locally and community engagement to influence relevant behaviours. Activities were planned to amplify the impact of the national and London-wide activities. WLWA had a general focus on food waste prevention activity from April 2012, but key activity was delivered from October 2012 onwards. Activities during the campaign period included:

Local radio adverts – radio adverts placed on LBC Radio in January 2013, followed by adverts on Radio Jackie, Hayes FM and Sunrise Radio in March 2013. The minimum reach of these adverts is estimated to be 1.1million people

Let’s Get Cooking Clubs – 28 Let’s Get Cooking Clubs were set up across West London, engaging 800 people. The purpose of the Clubs is to provide practical cookery skills and information to enable people to make the most of the food that they buy.

Internal communications – targeting staff within the boroughs of West London through internal magazines and the intranet at key points throughout the year. This activity took place in Ealing, Hounslow and Harrow, and targeted 9,000 staff members.

Social Media – WLWA delivered an on-going programme of social media, communicating directly with residents about LFHW. Between Sept 2012 and Mar 2013 99 LFHW related tweets were put out by WLWA.

Local online advertising – LFHW digital adverts included on the websites for local news, linked to the LFHW website to direct people to the national campaign. On Harrow Times and Richmond and Twickenham Times website gave 113,634 page impressions with 609 people clicking on the link and following through to LFHW.com.

Website – 9 articles were published on the WLWA website relating to LFHW with a direct link to the national website

Press Adverts and Advertorials in the local press/borough magazines – half page adverts were placed in four of the borough magazines, with half page adverts placed in the local press for the other two boroughs (for which borough magazines were not available). This activity was delivered in October 2012. A further round of press adverts ran in January 2013 across local press and one borough magazine. The local newspaper and borough magazines would have reached 689,445 people.

Vehicle Livery – LFHW vehicle livery on eight refuse vehicles in the London Borough of Harrow.

Posters – posters were displayed in local shops and community noticeboards to promote key messages.

Bus Adverts – 65 bus-back adverts were displayed for a period of 8 weeks, including 53 adverts which remained for 14 weeks, from October 2012.


Outdoor Adverts – Twenty-four 6 sheet adverts were placed across the six boroughs for a period of two weeks, and ten 4 sheet adverts were placed for 4 weeks, from October 2012.

European Week of Waste Reduction (EWWR) – there was a focus on food waste prevention during European Week of Waste Reduction (November 2012), through the local zero waste challenge run by WLWA. This challenged local residents to reduce their waste in general and food waste in particular in a number of different ways.

Roadshows / Community Engagement activity – WLWA delivered 50 roadshows and community talks, directly engaging 900 residents, providing information to residents primarily about food waste prevention but also included how to recycle their food waste and distributing 2,245 engagement resources. These events were primarily focused on waste prevention

PR – regular press releases to support local and London-wide activity. Unfortunately, as with the London-wide PR there was little media coverage.


3.0 Methodology This section details the methodology used for the household interviews and waste compositional analysis and explains WRAP’s approach to analysing the questionnaire responses in terms of the behavioural scorecard and food waste awareness. The two pieces of research were conducted by Exodus Research Ltd and Waste Intelligence Ltd respectively. 3.1 Methods for the household interviews The aim of the household interviews was to measure self-reported levels of behaviour and attitudes related to household food waste before and after the LFHW campaign in West London. In addition, these interviews also assessed the level of awareness of household food waste as an issue, and awareness of key materials used in the campaign. The post-campaign interviews also asked direct questions about whether the campaign had influenced practices and behaviours related to household food waste to those respondents who had seen messages relating to the campaign. The interviews also allowed informed consent to be obtained from all households to having their waste analysed in the compositional analysis as part of this research. This informed consent was obtained both pre- and post-campaign waves of the research. The interviews were conducted face-to-face in two waves:

Pre-campaign: 2,505 households surveyed between 3rd and 22nd September 2012; and

Post-campaign: 1,070 of these households were revisited between 2nd and 19th April 2013.

The number of post-campaign interviews is lower than those pre-campaign as the post-campaign research focused on those households interviewed pre-campaign that had consented to the waste analysis. This maximised the number of households for which pre- and post-campaign interviews has been conducted. The process for selecting households for the research is described in section 3.3, alongside the sampling for the waste compositional analysis. The interviews were carried out face-to-face for a number of reasons:

For the waste composition analysis to be feasible, the households involved in the research needed to be located in clusters. This precluded the use of other methods in which participants are geographically dispersed.

The research required informed consent from all households having their waste analysed in the compositional analysis element of the study. To facilitate this, researchers already had to visit participating households and therefore using a face-to-face questionnaire methodology was more efficient than other options (e.g. obtaining informed consent in person and then performing a telephone interview). Furthermore, informed consent levels are usually higher when asked towards the end of an interview where the interviewer has had the opportunity to build rapport with the interviewee.

To maximise the number of participants to ensure the robustness of the data all households that completed the post-campaign survey were offered a £10 high street voucher as an incentive to participate. A major aim of the questionnaires was to understand respondents’ practices and behaviours that can influence the amount and type of household food waste. The questions used drew heavily from WRAP’s regular household food waste consumer survey, which is conducted


twice a year. Where possible, the same questions have been used in the West London evaluation, although some modifications were required due to the West London survey being face-to-face and the WRAP consumer survey more recently has been conducted on-line. For this reason, the results in the West London are not directly comparable to the recent WRAP consumer survey data. A ‘behavioural scorecard’ was developed in 2010 for WRAP’s consumer survey that allows some of these key behaviours to be measured over time14. This scorecard is composed of nine behaviours (listed below) selected for their relevance to household food waste.

Planning meals in advance;

Checking levels of food in cupboard and fridge prior to shopping;

Making a shopping list;

Using the freezer to extend the shelf life of food;

Storing meat and cheese in appropriate packaging or wrapping;

Storing fruits and vegetables in the fridge;

Using up left-overs;

Portioning rice and pasta; and

Using date-labels on food.

These behaviours cover a large proportion of the activities that could reduce food waste and are broadly applicable to the majority of households in the UK (and also West London). Although this is not an exhaustive list, the behaviours may act as a proxy for wider behaviours (e.g. storing apples in the fridge, thereby increasing shelf life, is used as a proxy for storing other fruit in the fridge) and can be seen as an indicator of behaviour change. The full pre- and post-campaign questionnaires used for these household interviews are in Appendix C and D, showing the questions used to assess awareness and attitudes to food waste. As indicated previously, informed consent was gained from households willing to participate in this research during the interview process. Households were briefed face-to-face on the requirements of the study and given a letter from WRAP explaining this. A helpline number to enable residents to ask questions and opt out of participating in the research at any time was made widely available. Households that were part of the sample for the pre-campaign waste compositional analysis were re-contacted as part of the post-campaign interviews to obtain informed consent for the post-campaign waste compositional analysis. 75% of residents interviewed in pre-campaign and 88% of residents interviewed post-campaign provided consent to be included in the waste composition analysis. All information from the household interviews and the waste compositional analysis was treated in confidence and has been anonymised. Council services / helplines and the police were also notified that the work was taking place. Details of the households that had been interviewed and had provided consent were then forwarded to the waste analysis contractor, Waste Intelligence Ltd, so that the waste compositional analysis could be undertaken on households that had completed an interview and provided consent. Residents that provided consent were informed they may not be selected to be part of the sample and that the waste analysis could take place at any point in the next six months. Details of the methodology for the waste composition analysis can be seen in section 3.2.

14 Full details of the behavioural scorecard can be found at the link below (registration is required to view the documents, but this is quick and free): http://www2.wrap.org.uk/downloads/Consumer_food_waste_scorecard_-_guide_to_behaviours_FINAL_8_8_111.65b8df82.11986.pdf

http://www2.wrap.org.uk/downloads/Consumer_food_waste_scorecard_-_guide_to_behaviours_FINAL_8_8_111.65b8df82.11986.pdf

http://www2.wrap.org.uk/downloads/Consumer_food_waste_scorecard_-_guide_to_behaviours_FINAL_8_8_111.65b8df82.11986.pdf


3.2 Methods for waste compositional analysis The waste compositional analysis measured the food waste generated from a sample of households in West London before and after the LFHW campaign. This information has been used to aid evaluation of the impact of the campaign on its main aim: reducing food waste. 3.2.1 Waste streams sampled The sample of households for waste compositional analysis was drawn from three of the boroughs within the WLWA, namely Harrow, Hounslow and Richmond-upon-Thames. Sampling was not performed in the remaining three boroughs – Brent, Ealing and Hillingdon – for the following reasons:

The three boroughs chosen cover the waste collection schemes present in the WLWA (Table 2); and

To sample in all six boroughs would increase the cost of the research with only a negligible increase in the representativeness of the sample.

Table 2: Food waste collection type for boroughs in West London

Organics Collection Type

Borough

Collection frequency Percentage of W. London households receiving collection

type Food waste

Residual waste

Mixed garden and food

Brent Weekly Fortnightly 19% 33%

Harrow Weekly Fortnightly 14%

Separate food

Ealing Weekly Weekly 21%

50% Hounslow Weekly Weekly 16%

Richmond-upon-Thames

Weekly Weekly 13%

Restricted – fruit and veg peelings only with garden

Hillingdon Fortnightly Weekly 17% 17%

From within these boroughs, waste-collection rounds were selected and households were selected within these rounds to be representative of West London (see section 3.3 for more details). Waste compositional analysis was performed to measure food waste in the residual (general) waste stream and any council collections that target food waste (either separately or mixed with garden waste). Food waste within dry recycling (as a contaminant) only occurs at very low levels and this waste stream was not included in this research. Hounslow and Richmond-upon-Thames offer weekly collections of both residual and food waste, while Harrow offers fortnightly collection of residual waste and a weekly collection of mixed garden and food waste. For Harrow, a fortnight’s worth of waste was collected and sorted to account for any differences within the two-week cycle; for Hounslow and Richmond-upon-Thames, a single week’s worth of waste was collected and analysed.


Waste was collected and sorted from the participating household between the 1st and 10th October 2012 for the pre-campaign analysis and again between 13th and 22nd May 2013 for the post-campaign analysis. 3.2.2 Material classification When collected, an assessment was made of how full the households residual waste and food or food / garden bins were. The contents of the bin were then transferred into a leak-proof sack and each sack tagged with the unique ID code for that household. Each sack was individually hand sorted and the waste split into food and non-food with the food waste element classified and weighed as:

Avoidable food waste – the food has been thrown away because it is no longer wanted or has gone past its best (examples include an apple or half a pack of cheese);

Possibly avoidable food waste – food that some people will eat and others will not, or that can be eaten when prepared in one way but not in another (examples include bread crusts and potato skins); and

Unavoidable food waste – this arises from food preparation and includes foods such as meat bones and ‘hard’ fruit peelings (e.g. melon rind); it also includes used teabags and coffee grinds.

A fourth category for ‘unidentifiable’ was used only where absolutely necessary. Waste identified as avoidable was further categorised as either: fruit / vegetables; meat / fish; or cooked / prepared food. Food still in packaging was also quantified, measuring the weight of the food both including and excluding the packaging. This sorting of materials is consistent with the high-level categorisation used in other WRAP research focused on food waste (e.g. Household Food and Drink Waste in the UK). The current research does not go into the detailed classification of previous research; this choice was made to reduce the overall cost of the project. It does mean, however, that changes in the specific types of food waste (e.g. bread and apples) cannot be reported as they have not been measured. It is acknowledged that this study does not cover food and drink waste that is disposed of down the drain, home composted or fed to animals. The effect of the campaign on these disposal routes and the potential diversion of food waste to them cannot therefore be quantified. These disposal routes were not included as they represent a minority of total arisings and are more difficult to directly measure than waste collected by local authorities. Although asking a sample of people to record information in a kitchen diary is feasible, it would have increased the project budget considerably. In addition, including questions to try and quantify this via the questionnaire would have made the questionnaire too long; it was decided that measuring behavioural change via the questionnaire was a higher priority. 3.3 Details of sampling This section details the sampling approach and discusses the potential impact of the choices made on the results. The aim of the research was to obtain information as representative of West London households as possible. This allows the results to be generalised to all households in West London. However, it is important to note that there were a number of constraints on sampling that have the potential to impact on the representativeness of the sample:

The sample covered three of the six boroughs in West London;

The sample was clustered within 18 waste-collection rounds;


Physical access to certain properties was restricted (e.g. gated communities and some flats); and

No sampling from was performed from properties with bins that are shared between multiple households (i.e. where it is difficult to identify which waste came from which household).

As stated in section 3.2, three boroughs – Harrow, Hounslow and Richmond-upon-Thames – were selected for the research, as these covered the main waste-collection models operating in West London. Within these boroughs, a total of 18 waste rounds were selected (6 in Harrow, 9 in Hounslow and 3 in Richmond) that were closest to the demographic profile of West London, whilst accommodating the logistical needs of the project (i.e. collecting the waste and moving it to the sorting sites). This was assessed using MOSAIC15 profiling to identify the level of affluence associated with each waste-collection round. The households participating in this research were selected from these waste rounds. 2,505 households were interviewed pre-campaign and from these 836 were selected for the compositional analysis. After the household interviews had been completed the following categories were applied to each household to inform the selection for the compositional analysis:

Select - households that were suitably clustered (for logistical reasons) which had a demographic profile similar to that of all households in West London;

Backup - households that are not as close to the demographic profile of West London as hoped and should only be selected if those in the above category could not be used; and

Avoided - households that should not be analysed (e.g. had declined or opted out at a later date).

Therefore, the households selected for the compositional analysis were chosen for practical reasons (e.g. from streets than ran into each other to ensure the waste could be collected quickly before the council collection crews arrived) and met the required demographic profile where possible. For the post-campaign compositional analysis, it was important to obtain informed consent again and it was also important to identify households that had changed (e.g. moved) in the interim period. Therefore, the primary focus was to re-interview as many of the 836 households in the pre-campaign compositional analysis. Households were visited on at least three occasions on different days of the week and at different times of day over a three-week period to ensure as high coverage as possible. In total, 458 households of the 836 were successfully re-contacted and waste compositional analysis performed on their waste. The remaining households from the original 2,505 were also contacted for re-interview post-campaign – in total 1,070 were interviewed in the second round (which includes the 458 households included in the post-campaign compositional analysis). Where possible, the person who responded to the first interview was re-interviewed and this occurred in 974 of the 1,070 households (91%) in the post-campaign interviews. Where this was not possible, another adult from the household was interviewed. During the data cleaning process 5 households from the pre-campaign and 6 households from the post-campaign waste composition analysis were excluded due to uncertainty over the household surveyed and comments from the surveyors on the nature of the waste collected (e.g. suggesting that the waste was from multiple households or contained a large

15 Mosaic is a system for classification of the characteristics and lifestyles of UK households.


element of trade waste). This resulted in data from 831 households from the pre-campaign and 769 households from the post-campaign compositional analysis being analysed. Of these, 452 households were included in both the pre- and post-campaign compositional analysis allowing matched analysis to be carried out on these households.

Table 3: Sample sizes for difference elements of the research

Research element Sample size

Pre-campaign household interviews 2,505

Post-campaign household interviews 1,070

Paired sample for household interviews 1,070

Pre-campaign waste compositional analysis 831

Post-campaign waste compositional analysis 769

Paired sample for waste compositional analysis 452

Figure 1: Venn-diagram representation of samples for a) household interviews and b) waste compositional analysis

Household interviews

Waste compositional analysis

Not all of these participating households set out their residual-waste bin or their food-waste-collection receptacle. For the pre-campaign analysis, 127 household out of the 831 did not set out any bin during the sampling period, while 145 households (out of 769) did not for the post-campaign analysis. Households were not informed in advance of exactly when the research was taking place (i.e. which week their waste could be collected and analysed). Households not setting out waste were still included in the sample as analysis is performed on the average amount of food waste from groups of households. For residual waste, not setting out implies that the household has forgotten, is away or does not deem that it has sufficient waste to set out. In all these eventualities, for every household not setting out waste there should be an equal number setting out two weeks’ worth (or two fortnights’ worth) of waste (provided holiday seasons are avoided). Therefore, when calculating

Pre-campaign interviews: 2,505 respondents

Post-campaign interviews (and paired

sample): 1,070

Pre-campaign analysis: 831

Post-campaign analysis: 769

Paired sample:

452


averages it is important to include households not setting out, otherwise an overestimate of waste levels will be made. A similar argument holds for food-waste collections, with the additional consideration that not setting out may be an indication that a household does not use their food-waste collection at all (and any food waste generated will be in the residual stream, home composted or fed to animals). 3.4 Sample size, confidence levels and weighting The methodology described above has been designed to maximise the chance of observing any changes over the course of campaign. Revisiting the same households before and after the campaign allows a ‘paired’ statistical analysis to be performed on the data. This type of analysis involves investigating the distribution of differences in food waste arisings for the households involved, taking into account that we have pre- and post-campaign data from the same set of households. (An unpaired analysis would not take into account the fact that the data had been collected from the same households). Given the variation between households in the amount of waste generated, a paired analysis allows a greater opportunity to discern a change between the two waves of research for a given number of households. The statistical significance of differences in the two waves of research (pre- and post-campaign) is presented alongside key results in section 4.0. Within the constraints of the budget, the samples for the interviews and for the waste compositional analysis (as described in section 3.3) have been maximised. This means the statistical power of the ensuing analysis is as large as possible. Prior to commissioning the work, analysis of previous waste-compositional analysis data was performed to determine how many households would be required to observe different changes in food waste arisings16. The number of households required depends on the magnitude of the change in food waste arisings. For a sample of around 450 households – as we have in this study – it should be possible to detect a change of at least 11% in food waste arisings. As stated previously, there was no sampling from properties with shared bins. This allowed waste levels to be linked to specific households with known demographic information (in addition to other information collected in the interviews). However, this decision meant that the sample of households could not be fully representative of West London. This is especially true for the type of property, as flatted properties were largely omitted. As a consequence of this omission, the households included in the sample had slightly more occupants on average than for West London. Further details are available in section 3.4.1 and 3.4.2 where the options for weighting the data to account for demographic factors are discussed. The sampling that has taken place is designed to be representative of West London households, rather than the West London population. This is an important distinction when comparing the age and job status of the respondent in the interviews. Because interviews were preferentially conducted with people with responsibility for food shopping, cooking and food preparation, this means that some demographic elements are not in proportion to the population as a whole. For example, for multi-occupancy households containing people in the 18-24 age group, the 18-24 year olds were less likely to be responsible for shopping or cooking than the other (older) members of the household.

16 This internal analysis was based on the dataset behind Household Food and Drink Waste in the UK (WRAP, 2009)


Due to the short timescales of the project, it was necessary to conduct the interviews in English (sometimes with a family members or neighbours acting as interpreters if available). This has the potential to lead to a degree of unrepresentativeness for some ethnic groups. 3.4.1 Weighting of cases for the household interviews Given the differences between the sample and population mentioned above, it is possible to weight the results to correct for any under- or over-representation of a given part of the household population. Weighting helps to make the results from the sample reflect the population of West London more accurately. In this research, weighting was performed on a demographic variable if the following conditions are all met:

There is substantial over- or under-representation of a given demographic group;

There is a substantial difference between these demographic groups in the amount of food waste generated or other food-waste related factors (such as behaviours); and

There is high-quality data for the West London population and the sample to allow weighting factors to be calculated.

To aid this decision, values within the behavioural scorecard have been calculated for unweighted cases and cases weighted by:

Number of occupants in the household (household size);

Age of interview respondent;

Ethnicity of respondent;

Food-waste collection type (whether separate or mixed with garden waste);

Housing type; and

Presence of children in the household.

Neighbourhood profiling such as MOSIAC was also considered for weighting. However, previous analysis has not shown substantial differences in waste arisings relating to food between MOSAIC groups. Given their absence from the dataset, including MOSIAC as a potential weighting factor was not deemed a priority.

Table 4: Effect of weighting on average behavioural score (out of a possible score of ten)

Weighting: Behavioural

score

Change from unweighted score

Absolute %

Unweighted 6.53 – –

Weighted by household size 6.55 +0.02 +0.3%

Weighted by age 6.50 –0.02 –0.3%

Weighted by ethnicity 6.50 –0.02 –0.3%

Weighted by collection type 6.53 0.00 +0.1%

Weighted by housing type 6.49 –0.04 -–0.6%

Weighted by presence of children 6.51 –0.02 -–0.2%

For the average behavioural score for the post-campaign survey, the biggest change due to weighting was 0.05 (or 0.7%), a negligible change. For the nine individual behaviours (not shown in the table), most of the changes were small, the vast majority of the differences being under 3%. When weighting by housing type or ethnicity, some changes of 9% were found (one behaviour for housing type, two for ethnicity), although this is still relatively small.


Given the small influence of weighting, the criteria laid out above were not met. Consequently, weighting of the data was not performed on the household interview results.

3.4.2 Weighting of cases for the waste compositional analysis The same exercise was repeated for the waste compositional analysis to determine which factors, if any, to weight by. It was found that weighting by either household size (i.e. number of people in the household) or housing type influenced the results substantially (Table 5). Given the low number of flatted properties in the sample, it was not sensible to use housing type as a weighting factor, as the small number of flats included in the sample would be used to represent all flats in West London. Previous research17 has also demonstrated that the amount of food waste increases with household size. It was therefore decided to weight by household size. Weighting by household size partially circumvents this issue relating to little sampling from flats, as it adjusts the amount of food waste generated to take into account the under-representation of smaller properties in the sample. There is an implicit assumption that smaller properties in the sample (mainly houses) generate similar amounts of waste to smaller properties in the population (mainly flats).The authors are not aware of any published data that supports (or refutes) this assumption.

Table 5: Effect of weighting on total amount of household food waste (kg per household per week)

Weighting: Amount of food

waste (kg / hh / week)

Change from unweighted amount

kg / hh / week

%

Unweighted 2.48 – –

Weighted by household size 2.20 –0.28 –11.5%

Weighted by age 2.65 +0.17 +6.8%

Weighted by ethnicity 2.64 +0.16 +6.3%

Weighted by collection type 2.48 0.00 +0.1%

Weighted by housing type 1.99 –0.49 –19.8%

Weighted by presence of children 2.47 –0.01 –0.4%

Although age and ethnicity have a small but measurable impact on the results, it was decided not to weight by these variables. This is for two reasons. Firstly, age and ethnicity relate to individuals, not the whole household. Secondly, there are correlations between household size and these two variables, which, in the absence of interlocking population data, make weighting difficult. Although not included in the report, headline results have been calculated weighted by ethnicity and age: if the cases were weighted by these factors, it would not change the conclusions drawn from the study. Therefore, the waste compositional analysis data are weighted only using the household-size variable.



4.0 Results 4.1 Waste compositional analysis: changes in the amount of food waste This section presents the weighted results of the compositional analysis for the paired sample of 452 households that were included in both the pre- and post-campaign compositional analysis. The results compare the amount of food waste in kilograms per household per week (kg / hh / week). Further interpretation and discussion of these results is presented in section 5.0. Table 6 shows that the total amount of food waste decreased from 2.60 kg / hh / week pre-campaign to 2.20 kg / hh / week post-campaign. This is a reduction of 0.40 kg / hh / week (±0.36 kg / hh / week) or 15% (±14%). This reduction is therefore significant at the 95% confidence level but the degree of reduction has a high level of uncertainty associated with it. The majority of this reduction results from a decrease in food waste in the residual waste stream. While a small reduction is observed in the food waste collections, this is not significant.

Table 6: Average food waste per household per week in West London by disposal route.

Amount of food waste (kg / hh / week) Significance

of change Pre Post Difference %

Residual 1.22 0.91 –0.31 -26% >95%

Food waste collections 1.37 1.28 –0.09 -6% not sig.

Total 2.60 2.20 –0.40 -15% >95%


The results when analysed for avoidability are shown in Table 7. Both avoidable and unavoidable food waste reduced with avoidable food waste reducing by 0.17kg / hh / week (14%) and unavoidable food waste reducing by 0.27 kg / hh / week (24%). Therefore, the majority of the reductions in the food waste is due to decreases in unavoidable food waste and while there is a reduction in avoidable food waste this is only significant at the 85% confidence level. Further discussion of these results can be seen in section 4.3.

Table 7: Food waste by avoidability

Amount of food waste (kg / hh / week) Significance of

change Pre Post Difference %

Avoidable 1.24 1.07 -0.17 -14% c. 85%

Possibly avoidable 0.19 0.23 +0.05 +25% not sig.

Unavoidable 1.17 0.89 -0.27 -24% >95%

Total 2.60 2.20 -0.40 -15% >95%

Waste identified as avoidable was further categorised as either: fruit and vegetables; meat and fish; or cooked / prepared food. Table 8 shows the amount of food waste for these food categories. There is an 18% reduction in food waste for the cooked / prepared food category, and this accounts for the majority of the food waste reduction between the pre- and post-campaign waves with a 0.15 kg / hh / week reduction of the total avoidable reduction of 0.17 kg / hh /week. Only insignificant changes were observed for fruit and vegetables and meat and fish.

Table 8: Food waste by food category


change Pre Post Difference %

Fruit & veg 0.36 0.34 -0.02 -6% not sig.

Meat & fish 0.03 0.03 0.002 +6% not sig.

Cooked food 0.85 0.70 -0.15 -18% c.85%

Avoidable total 1.24 1.07 -0.17 -14% c.85%

It is acknowledged that the total amount of food waste is lower in this study than observed in previous research18. Furthermore, the proportion of avoidable waste is lower in the current

18The Synthesis of Food Waste Compositional Data 2010: http://www.wrap.org.uk/content/new-estimates-household-food-and-drink-waste-uk

http://www.wrap.org.uk/content/new-estimates-household-food-and-drink-waste-uk



research (48-49%) than other studies from the UK (around 60-65%)19. These two pieces of information are consistent with each other: households with lower levels of food waste tend to have a higher proportion of unavoidable waste (all other things being equal), as unavoidable waste is generated as a result of bringing certain foods (especially fruit, vegetables, meats and eggs) into the home, whereas there is considerable scope to reduce avoidable food waste. There are a number of possible explanations for these discrepancies: for example, household food waste in West London in 2012 may be genuinely lower than that in the UK in 2010. For instance, the amount of food eaten outside the home is higher in London than the rest of the UK20, suggesting that the amount eaten inside the home is less. Further, instances of sink disposal units may be higher in London (although the exclusion of flats from this research may counteract this), leading to more food waste going down the sink and less being collected by local authorities. Alternatively, it could result from the way the research has been conducted. For instance, the matched sample contains households that have given informed consent twice, and these households may generate less food waste than those that did not provide consent. The estimates from the Synthesis study are based on composition analysis of Local Authority waste where consent is usually not required, so are not likely to be affected to this potential effect to the same extent. If it is a methodological effect, this implies that the reductions in food waste seen occurred in households that already had lower waste levels. Arguably, these households have less potential to reduce food waste further as food-waste levels are already lower than the national average. A small group of people within the sample reported that they were strongly influenced by the campaign or other food-waste messages. Specifically, 14% of households interviewed after the campaign (148 out of 1,070) were both aware of the food-waste messages and said they were doing something different as a result. The waste compositional analysis for this group (62 out of the total sample for compositional analysis of 452) showed that they had reduced their food waste by an average of 1.1 kg / hh / week (a 35% reduction; Table 9); the reduction for avoidable food waste was 0.72 kg / hh / week (a 43% reduction). Although based on only 62 households (out of the total matched sample of 452), these reductions are significant at the 95% confidence level due to the magnitude of the reductions. This small group contributes around half of the total reduction in food waste of the sample. The households in this group of 62 are slightly larger (3.5 people per household) compared to those in the matched sample (3.1 people per household).


20 From Defra’s Family Food datasets, the 3-year average from 2009-2011 for food eaten outside the home is 614 grammes per person per week in London. Taking an average over the same period for the UK gives 521 g / person / week. (These estimates exclude the Family Food categories for drinks: beverages, soft drinks and alcoholic drinks).


Table 9: Average arisings of food waste from households who were aware of the food-waste messaging and said they were doing something differently as a result


change

Pre Post Difference %

Total food waste 3.16 2.07 –1.09 -35% >95%

Possibly avoidable 0.33 0.31 –0.02 –6% Not significant

Unavoidable 1.17 0.81 –0.36 –30% >95%

Avoidable food waste

1.66 0.94 –0.72 -43% >95%

4.2 Results from the household interviews As detailed in section 3.1, the household interviews were undertaken to understand the practices and behaviours of the interviewee and the influence of these on the household’s food waste. This section presents results for the nine key behaviours used for WRAP’s behaviour scorecard for the 1,070 households interviewed both pre- and post-campaign. The nine key behaviours are summarised in the behavioural scorecard in Figure 2 with each of the behaviours given a score between zero and ten; the behaviour response relating to the lowest level of food waste is given ten and that relating to the highest level of food waste given zero. From the pre-campaign interviews the average behaviour score was 6.2 and this increased to 6.5 based on the responses from the post-campaign interviews (Figure 2), a significant increase at the 95% confidence level. This shows a move towards behaviours that relate to less food waste over the period of the campaign. The largest changes in behaviours observed between the pre- and post-campaign relate to meal planning, list making, use of the freezer and storage of open cheese and meats.


Figure 2: Summary of Behavioural Scorecard

Figure 3 to Figure 13 present further details of each of the behaviours, including the levels of responses to the question that are used within the behavioural scorecard. 4.2.1 Meal planning For meal planning the summary scorecard (Figure 2) shows a change from 2.6 in the pre-campaign interviews to 3.4 in the post-campaign interviews. The responses in Figure 3 show that 59% gave the response of ‘I usually decide on the day’ pre-campaign and this reduced to 44% post-campaign. Increases in the level of responses were seen for ‘I know what a few of main meals will be for the next week’ with an increase of 7% in respondents giving this response, and a 6% increase for ‘I know what most of the main meals will be for the next week’. This suggests that levels of meal planning have increased in the sample, as reflected by the increased behavioural score.

Figure 3: Responses to interview question: To what extent do you decide what you are going to eat for main meals in advance? (only one response allowed).


4.2.2 Checking food stocks A small change from 8.3 to 8.4 is observed in the behavioural scorecard for checking cupboards for food stocks before shopping. Response levels to this behaviour are already high (Figure 4) and there are only minor changes to the response levels, suggesting that the degree of checking cupboards and other food stocks before a shop has not changed markedly over the period of the campaign.

Figure 4: Responses to interview question: Think about the last time you did a main grocery shop. Before a particular shop did you check what you already had at home for any of the following? (percentage shown is those answering yes).


4.2.3 List making Figure 5 shows the responses to the question on making grocery shopping lists; there has been a large increase in those keeping a running list which led to the increase in the behavioural score from 8.1 to 8.5. This increase was tempered by a slight reduction in those taking a list with them.

Figure 5: Responses to interview question: ‘Still thinking about the last time you did a main grocery shop do any of these describe what you did before that shopping trip?’ (Multiple responses are allowed)

4.2.4 Use of a freezer There was an increase in the behavioural score for the use of the freezer from 2.7 to 3.3, reflecting the fact that respondents froze more items after the campaign. For example 25% of respondents froze 3 or more items in the past week after the campaign compared to 19% before the campaign. Similarly, the number not freezing anything fell from 31% to 22%.

Figure 6: Responses to interview question: Excluding food that was frozen when you bought it, which of the following items have you put into the freezer in the past week?

Number of non-frozen items placed in the freezer


4.2.5 Storage of open cheese and meat Figure 7 and Figure 8 illustrate how respondents store cheese and meat once it has been opened. For both food items there were increases in the number of people using bags, boxes, film or foil to store opened items and fewer people using the original packaging. This is reflected in the behavioural scorecard, which increased from 6.3 to 7.3.

Figure 7: Responses to interview question: Think about the last time you opened an item of cheese. How did you store these after opening?’ (Multiple responses allowed)

Figure 8: Responses to interview question: Think about the last time you opened an item of sliced meat. How did you store these after opening?’ (Multiple responses allowed)


4.2.6 Use of the fridge to use fruit or vegetables Storing fruit or vegetables in the fridge can extend the shelf-life of many items, including apples and carrots. This question assesses how the respondents store apples and carrots. There was very little change in the levels of those storing either item in the fridge, and this was reflected in the behavioural score for this behaviour, falling slightly from 6.2 to 6.1.

Figure 9: Responses to interview question: Think about the last time you went shopping and purchased fresh apples or carrots or potatoes. When you returned home, where did you store it?’

4.2.7 Use of left overs Using up leftovers has the potential to reduce food waste. Figure 10 shows an increase in the percentage who said they used up leftovers either as part of a meal or as a meal in themselves. However, the amount that didn’t get used (and was thrown away) did not fall by very much, and this is reflected in the modest increase in the scorecard for this behaviour (7.4 to 7.5). This apparent contradiction is the result of people choosing more response options in the post-campaign interviews compared to the pre-campaign interviews – in this case, respondents were more like to choose both ‘used as part of a meal’ and ‘used as a meal in itself’ in the post-campaign survey. This may also be a result of an increase in ‘batch cooking’ where more food is cooked with the intension of the leftovers being used in another meal.


Figure 10: Responses to interview question: Thinking about the last time you had leftovers or made more food than you needed. What happened to those leftovers? (Multiple responses allowed).


4.2.8 Cooking the right amount Questions were asked to assess whether people are cooking the right amount of rice and pasta. Figure 11 shows that the number of people unintentionally cooking too much rice has gone up during the period of the campaign, whilst the number has reduced for pasta (Figure 12), leaving the overall behavioural score unchanged.

Figure 11: Responses to interview question: Think back to the last time you cooked a meal based on rice. At the end of the meal did you have any uneaten rice? (Only single response allowed).

Figure 12: Responses to interview question: Think back to the last time you cooked a meal based on pasta. At the end of the meal did you have any uneaten pasta?’ (Only single response allowed)


4.2.9 Use of date labels This question assesses how many of the respondents had thrown food away that was passed its use by date. Figure 13 shows that, both pre- and post-campaign, 56% of respondents had not thrown food away as a result of it passing the date on the packaging and there were only small changes in response for other number of items, leading to no significant change in the behavioural score for this question.

Figure 13: Responses to interview question: Over the past week have you thrown any of the following away because they have gone past the date on the packaging?

Number of items thrown away because they were past their date label


4.2.10 Self-reported waste levels Respondents were asked to quantify how much food they believed they were throwing away. Figure 14 shows that this has shifted to lower self-reported level of waste over the course of the campaign. For example, before the campaign, 42% of respondents stated that they throw away none or hardly any food; after the campaign, this had risen to 57%.

Figure 14: Responses to interview question: Thinking about the different types of food discussed in the previous question, how much uneaten food, overall, would you say you generally end up throwing away?


Figure 15 shows difference between the two waves of research for the perceived amount of food thrown away for a number of categories of food waste. This is calculated by giving responses relating to the highest level of waste (throwing ‘quiet a lot’ away) a score of 5 and the responses relating to lowest level of waste (throwing ‘none’ away) a score of 0 with the other response scored between these. The average is then calculated and difference between these pre- and post-campaign is then calculated. This shows a reduction in the perceived amount of food thrown away for 9 of the 15 categories (8 of these reductions are significant at the 95% level). For example, for cheese and yoghurt the score pre-campaign was 0.39 and post-campaign was 0.31, a reduction of 0.08. Many of the largest changes are associated with the food towards the end of its journey in the home: ready meals, homemade meals, and leftovers (i.e. food where too much was cooked or prepared but wasn’t served and food left on the plate after the meal). This is broadly consistent with the increased engagement seen in meal planning (Figure 3). Furthermore, ready meals was the only food to see a significant increase in the proportion of the population checking stocks before going shopping (Figure 4).

Figure 15: Responses to interview question: Over the LAST WEEK, how much of the following foods have you thrown away (in a compost bin, ordinary bin, council collection, down the sink or fed to pets etc.)? Scored on a scale of 0 to 5. * indicates statistically significant difference at 95% confidence level.


4.3 Results from WRAP’s regular household food waste consumer survey In addition to bespoke research for the West London evaluation, WRAP also conducts a regular household food waste consumer survey. This is conducted using on-line panels with a sample that is representative of Great Britain (effective sample size = 2,600-2,900, dependent on wave). The sample is boosted in London to achieve an effective sample size of around 1,000 in the Capital. Of interest to this research, waves were conducted in November 2012 and April 2013, roughly spanning the time of the campaign. Results for these two waves are shown in Table 10 for West London, London, and the Great Britain.

Table 10: Headline results from WRAP regular food waste consumer survey

Weighting details: West London London Great Britain

Nov ‘12 Apr ‘13 Nov ‘12 Apr ‘13 Nov ‘12 Apr ‘13

Effective sample size 175 183 960 1029 2622 2891

Average behavioural score 6.16 6.13 6.12 6.06 6.26 6.28

% heard about food waste in the last 12 months

33% 35% 31% 36% 30% 35%

The relatively small sample size in West London would only allow large scale changes to be picked up. For example, the change seen in behavioural scorecard between the pre- and post-campaign in the current research (6.2 to 6.5) is unlikely to be picked up. However, no significant change was seen in behavioural score for London, which, given the larger sample size implies that no major shift occurred in London as a whole. (Of contextual interest, the behavioural score in Great Britain exhibited no significant change.) There is evidence of an increased awareness of food-waste related information in London, with an increase in this awareness measure of five-percentage points. However, given a similar increase in Great Britain, this does not provide evidence that this increase of awareness was linked to London-specific campaign activities. Given the nature of the WRAP regular food waste consumer survey, no measurement of actual waste streams was undertaken. In summary, the information from the consumer survey is inconclusive for West London due to a small sample size.


5.0 Discussion of results The results in the previous two sections have demonstrated that those in the sample wasted less food after the campaign compared to beforehand. Furthermore, this was accompanied by positive changes in many of key behaviours associated with less food waste. These two results are consistent with each other. There are a number of possible explanations for these changes:

The campaign was effective, successfully encouraging people to change key behaviours and reduce their food waste;

Seasonal trends in food waste led to less being thrown away in May (post-campaign) compared to October (pre-campaign). This seems unlikely because:

1) seasonal trends in amount of food purchased are small (see Appendix B – section on Seasonal impacts) and consequently seasonality in arisings is likely to be similarly small; and 2) little seasonal variation has been seen in behaviours associated with food waste in other research (notably WRAP’s food waste consumer survey results), therefore behaviours are unlikely to be affected substantially by the timing of research within the year.

Food price inflation and / or changes in income have altered behaviour relating to food waste. Again, this does not appear to explain a large proportion of the change (econometric modelling indicates changes in incomes and prices are likely to have reduced food waste by around 1% at most), as food prices have risen at a rate similar to the last few years and income levels are relatively stable (see Appendix B, section on Impact of economic factors); and

A research effect: in short, carrying out two household interviews (and gaining consent for composition analysis) may have caused some (or all) of the change seen – see discussion below.

The inclusion of a control group within this study was considered cost prohibitive; it would have approximately doubled the cost of the fieldwork, which accounted for the vast majority of the project budget. Furthermore, it would have been practically difficult to construct a control group: i.e. matching the intervention and control samples would be complex, not least because geographical proximity would not be possible given the commitment to deliver a pan-London campaign. Had a control group been included, it may have been possible to distinguish between an effective campaign and the other three effects listed above. The calculations in Appendix B suggest the changes seen are unlikely to be due to seasonal effects or economic factors. However, it is not possible to rule out some influence of the ‘research effect’, whereby the act of being interviewed twice affects the behaviours targeted and waste levels. The research effect could potentially manifest itself in a number of ways:

Respondents giving interview responses that they deem more sociably desirable; (in this case, giving more sociably desirable answers in the second wave of interviews compared to the first);

The interview process increasing the salience of food waste for the sample and therefore increasing the likelihood that people are aware of the campaign and behaviour change occurs;

The interviews alone raise awareness and change behaviours, ultimately leading to less food waste.

The fact that food waste levels were lower in the post-campaign compositional analysis would suggest that the first point above – giving a more socially desirable response – is not the main manifestation of any research effect. Given that the compositional analysis is recording what food is actually in the waste stream (rather than a stated level of wasted


food), it is not as susceptible to social desirability (although the practice of providing informed consent may influence what a person disposes of). However, it is possible that the second and third points are in operation. The lack of change in the behavioural scores for London as measured in WRAP’s regular consumer food waste survey points to some of the effect from the current research being associated with the research effect. However, given the confidence intervals associated with both pieces of research, this is not conclusive evidence and does not allow quantification of the research effect. 14% of the sample said that they have seen or heard about food waste and that this had influenced the amount they wasted. As can be seen in Table 9, this group of people have made large reductions in the amount of food they waste. Given that the respondents were attributing this change to the images and messages they had seen about food waste, it seems fair to assume that the campaign is responsible for at least some of the changes seen, given the level of the campaign in West London. There could also be further impacts of the campaign outside the group who said they had been affected: other people who made changes may not have been aware of external influences (including the campaign) on their actions or decisions relating to food waste prevention. The total reduction in food waste is 0.40 kg / hh / week, and of this 0.27 kg / hh / week is unavoidable waste (for example used tea bags, bones and hard fruit and vegetable peelings etc). It is not clear why the majority of the reduction relates to unavoidable food waste but Figure 10 shows an increase in the number of people using leftovers as a meal or as part of another meal, this could suggest a change in cooking practice with ‘batch cooking’ contributing to the reduction in unavoidable waste (with less food being prepared from scratch as a result of not wasting as much of the food that is cooked resulting in less unavoidable preparation waste). In addition other factors involved are likely to include changes in cooking practices (less home cooking), altered purchasing patterns (change to purchasing food that is not prepared at home) and potentially seasonality (less unavoidable waste produced from foods purchased in May than October, e.g. more root vegetables are purchased during autumn and winter than spring and summer). Of the 0.17 kg / hh / week reduction in avoidable food waste, 0.15 kg / hh / week relates to the cooked food category. This is consistent with the self-reported changes shown in Figure 15 and behaviour changes shown associated with meal planning (Figure 3) and leftovers for other meals (Figure 10). The largest changes for individual behaviours related to planning (meal planning and list making) and storage (use of the freezer and wrapping of opened cheese and meats). These may indicate the behaviours which are most susceptible to change from a campaign or other intervention. A LFHW campaign in the city of Worcester was monitored by Worcestershire County Council21 without any household interviews (i.e. only waste compositional analysis was performed with households being contacted 6 to 8 weeks before the analysis giving them the option to opt-out of the study). This saw a similar reduction in total and avoidable food waste (around 15%). In such a situation, the research effect is less likely as households were only contact once by letter informing them of the analysis and giving them the option to opt-out.

21 http://www.wrap.org.uk/sites/files/wrap/2011.11_Worcestershire_CC_LFHW_2011_case_study.3e14035c.11397.pdf

http://www.wrap.org.uk/sites/files/wrap/2011.11_Worcestershire_CC_LFHW_2011_case_study.3e14035c.11397.pdf


It is acknowledged that during the campaign period in West London the London-wide and Nationwide LFHW campaigns continued with the same message used in West London. Therefore, these campaigns may also have impacted on the reduction in food waste observed in West London. There is a high degree of uncertainty around the changes observed: for instance the 95% confidence range for the reduction in food waste is from 0.04 to 0.76 kg per household per week (around a central estimate of 0.40 kg / hh / year). This high level of uncertainty is partly due to a lower matched sample than originally envisaged: 452 households were sampled both before and after the campaign. This was due to a smaller proportion of the households from the pre-campaign compositional analysis being successfully contacted to consent to the post-campaign compositional analysis, despite multiple attempts by the contractors to contact these households. This means that, although there is strong evidence (i.e. significant at the 95% confidence level) that a change in food waste has occurred within the sample, there is a large amount of uncertainty in the actual value, as reflected in the confidence range quoted above.


6.0 Potential cost and environmental savings The amount of food waste decreased by 0.40 kg / household / week between the pre- and post-campaigns compositional analysis and by 0.17 kg / hh / week for avoidable food waste (Table 6). If these changes are scaled up to all households in the six boroughs of West London it is equivalent to a reduction of 12,350 tonnes per annum for all food waste and 5,250 tonnes per annum of avoidable food waste. To purchase this avoidable fraction of food and drink waste would cost the residents of West London approximately £14.2 million per year22. The greenhouse gas emissions associated with the reduction of 5,250 tonnes of avoidable food and drinks waste is equivalent to 20,000 tonnes of carbon dioxide equivalents. With landfill tax currently costing £72 per tonne, the reduction in avoidable food waste would offer savings of almost £378,000 in landfill tax and assuming a total disposal cost of £106.50 per tonne this reduction would save the boroughs of West London £559,000 per annum in disposal costs (including gate fees and landfill tax). The reduction in total disposal costs for all food waste is £1.3 million23. It is likely that the campaign will have mainly affected avoidable food waste: the campaign did not focus on behaviours or decisions relating to the unavoidable fraction of food waste. Furthermore, a proportion of the reduction could be related to the research effect, whereby the act of being interviewed has an influence on behaviours and waste levels. Therefore, the results presented should be seen as an upper limit on the impact of this campaign.

22 Based on a cost to consumers of £2,700 per tonne. New estimates for household food and drinks waste in the UK, Nov 2011 (http://www.wrap.org.uk/content/new-estimates-household-food-and-drink-waste-uk).

23 The disposal charge during the period of the campaign was £93 a tonne. The current disposal charge is £106.50 and has been used for the purposes of this report.



7.0 Conclusions and Recommendations The aim of this research was to investigate and quantify the outcomes of the Love Food Hate Waste campaign in West London that ran from autumn 2012 to spring 2013. The results from the composition analysis showed a statistically significant reduction of 0.4 kg per household per week (a 15% reduction) in food waste arisings between the pre- and post-campaign analyses. The majority of this reduction is a result of decreases in food waste in the residual waste stream. For households saying they were doing something different as a result of seeing food-waste related messages (14% of the total number of households), the reduction in avoidable food waste was 43%. The use of a matched sample increased the ability of the analysis to discern changes between the pre- and post-campaign results. However, the matched sample was smaller than planned (see section 5.0 for details), leading to a large confidence interval around the observed reduction (0.4 ± 0.36 kg per household per week). This also means that few changes in sub-fractions of this total are statistically significant. Overall, a move towards behaviours, that relate to less food waste, over the period of the campaign was evident. The largest changes in behaviour relating to less food waste were for behaviours concerning meal planning, list making, use of the freezer and storage of cheese and meat. The impact of seasonal effects and economic factors on these results are only likely to have had a small impact on the results. However, it is not possible to rule out the ‘research effect’ having an impact on both the behaviour of, and food wasted by, participants in the study. The results therefore need to be considered in light of this and the figures quoted as an impact of the campaign should be considered as an upper limit. There was not sufficient budget for a control group within this research project. In light of the discussion on the potential impact of the research effect, a control should be considered for future research as it will help to understand the likely impact of other factors (see Appendix B). In particular, the potential effect that the research itself has on the results is not well understood; further insights in this area would be beneficial. In conclusion, the LFHW campaign was successfully investigated and information obtained to help quantify its impact. However, the absence of a control group means that these findings are not unequivocal and need to be interpreted alongside other information.


Appendix A: Peer Review Statement

The aim of the evaluation project was to ‘to investigate and quantify the outcomes of the LFHW campaign in West London that ran from autumn 2012 to spring 2013’.The purpose of the peer review was to review the final evaluation report, identify issues for clarification and discuss these with the report authors, with a view to forming an independent conclusion on the relevance, consistency and robustness of the research. The final report is well written and structured and provides a transparent description of the evaluation methods, results and conclusions. All of the issues identified have been clarified to the satisfaction of the peer reviewer. This allows me to conclude that the contents of the report are relevant to the aims of the project and that the research is consistent and robust. The following issues were identified for discussion and clarification with the report authors: Methodology: issues discussed and clarified with the authors included clustering of households for the waste compositional analysis as a potential source of bias, the possibility of having included questions on food and drink waste that is disposed of down the drain, home composted or fed to animals and how socio-demographic profiling was used to select houses for sampling. Results: the report was revised to identify higher levels of kitchen waste disposal units and eating out in London as possible factors in the lower levels of the total amount of food waste (at a household level) in this study than observed in previous research. Conclusions and Recommendations: the report draws careful conclusions, stating that ‘it is not possible to rule out the ‘research effect’ having an impact on both the behaviour of and food wasted by participants in the study. The results therefore need to be considered in light of this and the figures quoted as an impact of the campaign should be considered as an upper limit’. The report was revised to provide an explanation of why a control group was not included in the study, stating ‘it would have approximately doubled the cost of the fieldwork, which accounted for the vast majority of the project budget. Furthermore, it would have been practically difficult to construct a control group’. Dr Robin Curry Peer reviewer. 28th August 2013


Appendix B: Discussion of Factors that

may Influence Results

Other potential impacts on behaviours and food waste As well as the impact of the LFHW campaign and the research effect (as discussed in section 5.0) there are a number of other factors that could influence behaviours and household food waste. These include (but are not limited to) the collection system for waste, food prices, food price inflation and seasonality. This section discusses these factors and attempts to quantify their impact. Impact of changes to waste collection It is unlikely that changes in waste collection have influenced the results. This is because:

None of the boroughs taking part in this research changed collection methods during the time period of the study;

There is no strong evidence that the way in which household waste is collected (e.g. frequency of collection, presence of food waste collections) impacts on the quantities and composition of food waste collected24.

Therefore, changes to waste collection are unlikely to have impacted the results of this study. Impact of economic factors and econometric modelling Two economic factors have been shown to influence food waste: food-price inflation and income levels25. This section looks at these factors of the time period of interest. There are no regional data on either food prices or incomes for West London published at the time of writing. Therefore, UK data have been used as a proxy (UK-wide Average Weekly Earnings index). Similarly no West-London specific food-price data are available and UK food price data (from the consumer price index; CPI26) have been used (Figure 16). For the period September 2012 to May 2013, this reveals that:

Real earnings, relative to the long term trend, fell by 2.8%.

Real food prices, relative to the long term trend, rose by 2.3%.

24 WRAP’s most recent research on this can be found at: http://www.wrap.org.uk/content/food-waste-messages-maximum-impact-uk

25 Britain, Erik, Brigden, Andrew, Dixon Smith, Liz and Mitchell, Peter (2010) WASTE 2010: The Economics of Food Waste. In: Waste 2010 Conference (http://warrr.org/751/). Further work exploring this will be published Winter ’13 (CFP101-008).

26 http://www.ons.gov.uk/ons/datasets-and-tables/data-selector.html?dataset=mm23

http://www.wrap.org.uk/content/food-waste-messages-maximum-impact-uk

http://warrr.org/751/

http://www.ons.gov.uk/ons/datasets-and-tables/data-selector.html?dataset=mm23


Figure 16: Consumer Prices Index (CPI) for food and all items during the time-period of the campaign (Indexed, October 2012 = 100)

Source: Office of National Statistics (ONS)

As a result of price rises and other economic changes, food expenditure patterns are likely to have shifted, not only in terms of quantities and types of food, but also the proportion of food eaten in the home. However, from just the information above it is not possible to determine the level of change in food waste associated with these economic factors. To help quantify this, an existing econometric model linking these factors to food waste has been used. WRAP previously funded research to develop an econometric model, which investigates the interaction between household incomes, food prices, household awareness of food waste and the amounts of food both purchased and wasted27. Previously, this model has been used to produce projections for household food waste for a number of scenarios relating to:

Global economic growth;

Global commodity and food prices;

The relative performance of the UK economy;

Retailer profit margins; and

Awareness of food waste issues.

The model has been rerun over the time period of the campaign (September 2012 to May 2013) to determine what the effect of food-price inflation and income levels was on waste levels in West London. This creates a counterfactual against which the measured change in food waste can be compared. This modelling work indicated that, due to the changes in incomes and prices, food purchases – and by extension food waste – are likely to have reduced by around 1%. Therefore, based on this model, economic factors do not appear to explain the 15% change in food waste observed in the waste compositional analysis. It is also of interest to note that the econometric model predicts, given the approximate level of expenditure on the LFHW campaign in West London (£0.21 per household) and



the effectiveness of previous spend on similar campaigns, that food waste levels should reduce by around 12%, similar to the 15% measured through compositional analysis. Seasonal impacts As described above, the pre-campaign household interviews and waste compositional analysis were carried out in September and October 2012 with the post-campaign fieldwork being carried out in April and May 2013. The effect of completing the fieldwork at different times of year on the amount of food waste is explored in this section. Two pieces of information can be used to determine the importance of seasonality. The first is based on analysis of waste data, the second on seasonal trends in food purchasing. These appear to show differing effects, making a firm conclusion difficult. Analysis of seasonal variation of food waste arising from 100 compositional data sets was conducted as part of the Synthesis of Food Waste Compositional Data 201028. This research concluded that mean arisings in autumn (September, October, and November) exceeded arisings in other seasons by 8 to 10%. However, the confidence interval around this uplift is high, so although the difference is statistically significant at the 95% confidence level, the true value could be as low as 1-2% or as high as 16%. Analysis has also been performed by WRAP to investigate the seasonal variation in household food and drinks purchases using data from the Family Food Survey commissioned by Defra29. This analysis was based on monthly data for the period January 2001 to December 2011. The data analysis involved performing a simple form of time-series analysis. This was necessary to take into account long-term trends in purchasing30. For the example of potatoes, there is a reduction of around 20% in purchases over the 10-year period analysed. For a given group of food or drink, a trend-line was fitted to the data; a second-order polynomial trend-line provided a good approximation to the actual data and was therefore used for this analysis. Although there are large differences between the seasonal patterns for certain food types purchased (e.g. more potatoes are purchased during autumn and winter than spring and summer), the difference between the total purchased for all food types is relatively small with more purchased during the summer and in December than in Spring and Autumn (Figure 17) . For the months when fieldwork for this project was undertaken, Figure 17 shows that in April and May the food purchased is 0.8% and 0.1% less than the long term trend respectively, while in September and October they are 1.1% and 1.0% less than the long term trend respectively. The compositional analysis was carried out in October 2012 and May 2013 and analysis of the total food purchased indicates that on average 0.9% less food is purchased in October than in May, suggesting little variation in the total amount of food entering the home.

28 Appendix A: Analysis of seasonal variation in food waste arisings. http://www.wrap.org.uk/sites/files/wrap/Synthesis%20of%20Food%20Waste%20Compositional%20Data%202010%20FINAL.pdf

29 More information on this survey can be found at: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/family-food-statistics

30 For instance, if purchases had declined steadily between 2001 and 2011 but without a seasonal variation, the average purchases in January would be lower than the December average because of this trend. Therefore, a simple analysis of the average values from each month would erroneously show a seasonal effect. The time-series analysis presented here avoids this issue.

http://www.wrap.org.uk/sites/files/wrap/Synthesis%20of%20Food%20Waste%20Compositional%20Data%202010%20FINAL.pdf

https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/family-food-statistics

https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/family-food-statistics


Assuming the proportion of purchases that are wasted is approximately constant through the year, this result implies that waste levels are not highly seasonal. More detailed analysis was performed taking into account the seasonality of different food types (results not shown) and this resulted in a similar conclusions: little seasonal variation in food waste assuming a constant proportion of purchases becoming waste. These two results – from the Synthesis report and analysis of the purchasing data – appear in conflict with each other. There are a number of potential explanations:

Some food grown in the home or on allotments does not enter the household but is thrown away directly from gardens. For example, a large number of windfall apples could be thrown away directly. This would be measured in the compositional analysis, but not recorded in the Family Food Survey as this food would not have entered the home.

Seasonal variation seen in Synthesis report is towards the lower end of the confidence interval.

The proportion of purchases that are wasted is not constant through the year, with a greater proportion of purchases wasted in the autumn.

It should also be noted that the results of the pre- and post-compositional analysis only show a small reduction in fruit and vegetable waste (0.02 kg / hh / week), the food category most associated with seasonal variation but the cooked food category, where you would not expect much seasonal variation, shows a reduction of 0.15 kg / hh / week between the pre- and post-composition analysis. Given the above, there is not strong evidence that a seasonal effect is affecting the results, but further research would be beneficial in this area.

Figure 17 : Average residual for each calendar month showing the seasonal variation taking into account long-term trends

Considerations for future research In light of the discussion on the impact of the campaign and any research effect, modifications to the design of future research of this nature could be made. Where budget allows, a control group could be included, in an area matched to the intervention area but where food-waste interventions are at a minimum. This would allow the combined impact of the research effect, seasonality and economic factors to be assessed and an impact net of these effects could be determined.


However, resources often preclude this possibility. The alternative is to have an unpaired sample – i.e. to include different households in the pre- and post-campaign samples. This has the advantage that, if a research effect does occur, it is likely to be of the same magnitude in the pre- and post-studies, as, for each set of households, it will be their first (and only) interview. Therefore, any change seen would not be ascribable to the research effect. However, this reduces the ability of the analysis to discern any changes between the two waves of the research, as unpaired analyses are less sensitive than paired analysis. Furthermore, the two samples would need to be carefully matched to ensure comparability. In short, there are alternatives to performing a paired analysis on a group that has been involved in both pre- and post-campaign research. For future research the pros and cons of these alternatives need to be weighed up against the research objectives to decide on the most appropriate research design.


Appendix C: Pre-Campaign Questionnaire

Q1a. How responsible are you for food shopping in your house? Q1b. And how responsible are you for the preparation and cooking of food in your house?

I have responsibility for all or most of it

I have responsibility for about half of it

I have responsibility for less than half of it

I’m not responsible for any of it Q3. Which of these statements best describes your food shopping habits? READ OUT. SINGLE CODE

I buy almost all my food in a main shop. Go to Q4

I buy some food in a main shop and some in “top-up” shops. Go to Q4

I mostly buy food in smaller “top-up” shops. Go to Q4b Q4. And which of these statements best describes your food shopping habits? READ OUT. SINGLE CODE

I do a main shop more than once a week

I do a main shop about once a week

I do a main shop about once a fortnight

I do a main shop about once a month

I almost never do a main shop Q4b. Where do you normally shop? ALLOW MULTCODING

Aldi

Asda

Budgens

The Cooperative (Co-op)

Farm Foods

Iceland

Lidl

Marks & Spencer

Morrison’s

Sainsbury’s

Somerfield

Tesco

Waitrose

Online (specify) Other (specify)

Q5. To what extent do you decide what you are going to eat for main meals in advance? READ OUT. SINGLE CODE

I know what almost all of the main meals will be for the next week

I know what most of the main meals will be for the next week

I know what a few of the main meals will be for the next week

I usually decide on the day Q6. Please think about the last time you did a main grocery shop. This might include shopping in a supermarket, grocery store or on-line. Before that particular shop, did you check what you already had at home for any of the following? READ OUT FOOD ITEMS, SINGLE CODE EACH ITEM. DO NOT ASK THOSE THAT ANSWERED TO 4b “I almost never do a main shop”

ITEM YES NO Don’t know/can’t remember I don’t buy this food

A. Fruit 01 02 03 04

B. Vegetables 01 02 03 04

C. Bread 01 02 03 04

D. Fresh meat 01 02 03 04

E. Fresh fish 01 02 03 04

F. Milk 01 02 03 04


G. Ready meals 01 02 03 04

H. Tinned or dried food 01 02 03 04

I. Frozen food 01 02 03 04

J. Salads/leaves 01 02 03 04

Q7. Still thinking about the last time you did a main grocery shop, which of the following describe what you did beforehand? READ OUT. ALLOW MULTCODING. DO NOT ASK THOSE THAT ANSWERED TO 4b “I almost never do a main shop”

I kept a “running list” during the week of things I needed to buy

I made a list to take to the shop with me

I had a very clear list in my head

I had some idea of the kind of things I wanted to buy

I shop online and I used ‘my favourites’ to remind me what to buy

None of the above

Don’t know / can’t remember Q8. Still thinking about the last time you did a main grocery shop which of the following best describes what you did in the shop? READ OUT. ALLOW MULTCODING. DO NOT ASK THOSE THAT ANSWERED TO 4b “I almost never do a main shop”

I bought everything on my list

I bought most things on my list

I bought some things on my list

I bought some extra items not on my list

I bought quite a lot of extra items not on my list

I mostly decided what to buy as I did the shopping

I usually buy the same things each week

Don’t know / Can’t Remember

Not applicable ASK ALL Q11. Excluding food that was frozen when you bought it, which of the following items have you put into the freezer in the past week? READ OUT. ALLOW MULTICODING

Uncooked fresh meat or fish

An unfrozen ready-meal

Fresh bakery products

Any foods at or near their use by date

Fresh milk

Leftover cooked meat or fish

Homemade meals

Other items

Nothing

Do not have freezer or freezer compartment

Can’t remember / Don’t know Q12a and 12b. I’d like you to think about the last time you opened CHEESE / SLICED MEAT. How did you store these after opening? ALLOW MULTCODING

A. Cheese B. Sliced meat

In the original packaging 01 01

In a plastic bag (e.g. sandwich or freezer bag) 02 02

In a plastic box (e.g. Tupperware) 03 03

Wrapped in clingfilm or foil 04 04

Other form of wrapping or packaging 05 05

With no wrapping 06 06

I don’t eat this food 07 07

Don’t know / not applicable 08 08

Q13.I’d like you to think about the last time you went food shopping and purchased fresh apples. When you returned home, where did you store them? ALLOW MULTCODING

• In a fruit bowl


• In a cupboard • On shelf • On worktop • In fridge • Other • Don’t know / can’t remember • Don’t buy / store fresh apples

Q14. And thinking about the last time you went food shopping and purchased fresh carrots. When you returned home, where did you store them? ALLOW MULTCODING

• In a fruit bowl • In a cupboard • On shelf • On worktop • In fridge • Other • Don’t know / can’t remember • Don’t buy / store fresh carrots

Q16.Thinking about the last time you had leftovers or made more food than was needed, what happened to those leftovers? ALLOW MULTCODING

Used as part of another meal

Used as a meal in themselves

Didn’t get used and were thrown away

Fed to animals

Still being stored

Other specify

Don’t know / can’t remember

Don’t have leftovers Q17. Please think back to the last time you cooked a meal based on rice. At the end of the meal did you have uneaten rice left over? SINGLE CODE

Yes, deliberately cooked too much for another meal Yes, unintentionally cooked too much No, none left over Don’t know / can’t remember I don’t cook rice

Q18. Now think back to the last time you cooked a meal based on pasta. At the end of the meal did you have uneaten pasta left over? SINGLE CODE

Yes, deliberately cooked too much for another meal Yes, unintentionally cooked too much No Don’t know / can’t remember I don’t cook pasta

Q19.Over the last week, have you thrown any of the following away because they have gone past the date on the packaging? READ OUT. ALLOW MULTCODING

YES NO Don’t know / can’t remember

Do not buy this food

A. Fresh meats 01 02 03 04

B. Precooked meats 01 02 03 04 C. Milk 01 02 03 04 D. Yoghurts 01 02 03 04 E. Ready meals 01 02 03 04 F. Fruit juices 01 02 03 04 G. Bread or other bakery 01 02 03 04


YES NO Don’t know / can’t remember

Do not buy this food

items

H. Fresh fruit 01 02 03 04 I. Vegetables 01 02 03 04 J. Frozen items 01 02 03 04 K. Any other items 01 02 03

Q20. Over the last week, how much of the following foods have you thrown away (either in a compost bin, ordinary bin, council collection, down the sink or fed to pets etc.)? ROTATE STATEMENTS, SINGLE CODE FOR EACH STATEMENT

Quite a

lot

A reasonable

amount

Some A small

amount

Hardly

any

None Don’t

eat this

A. Fruit 01 02 03 04 05 06 07

B. Vegetables or salad 01 02 03 04 05 06 07

C. Bread and cakes 01 02 03 04 05 06 07

D. Raw or home cooked meat & fish 01 02 03 04 05 06 07

E. Cheese and yoghurt 01 02 03 04 05 06 07

F. Milk and fruit juices 01 02 03 04 05 06 07

G. Ready meals or convenience foods 01 02 03 04 05 06 07

H. Homemade meals 01 02 03 04 05 06 07

I. Parts of food not normally eaten (e.g. peelings, bones)

01 02 03 04 05 06 07

J. Food you cooked or prepared too much of but didn’t serve up

01 02 03 04 05 06 07

K. Food left on the plate after the meal 01 02 03 04 05 06 07

L. Foods bought but not used at all (e.g. unopened packs; whole fruit)

01 02 03 04 05 06 07

M. Food from packs that have been opened but not finished (e.g. slices of ham, bread rolls, cooking sauce etc.)

01 02 03 04 05 06 07

N. Food that’s gone off or mouldy 01 02 03 04 05 06 07

O. Food that’s gone past its use by date 01 02 03 04 05 06 07

Q21. Thinking about the different types of food discussed in the previous question, how much uneaten food, overall, would you say you generally end up throwing away? SINGLE CODE

Quite a lot

A reasonable amount

Some

A small amount

Hardly any

None

Don’t know Q22. Thinking about when you have thrown food away, how is it disposed of in your home? ALLOW MULTICODING

In the general refuse bin

Home compost bin

Food waste digester

Home wormery

Council food waste collection

Down the sink/drain

Fed to animals (pets, birds)

Other (do not specify)

Don’t know Q23. What do you understand the term ‘USE BY DATE’ on a food product to mean? READ OUT. SINGLE CODE

It depends on the food


It will be at its best quality before this date but is not necessarily unsafe

It will be safe to eat up to this date, but should not be eaten past this date

It’s not relevant to me, I can ignore the date

Don’t know Q24. What do you understand the term ‘BEST BEFORE DATE’ on a food product to mean? READ OUT. SINGLE CODE





Don’t know Q25. What do you understand the term ‘DISPLAY UNTIL DATE’ on a food product to mean? READ OUT. SINGLE CODE





Don’t know Q26. To what extent do any of the following encourage you to try to minimise the amount of food that your household throws away (into the bin, compost bin or council collection)? ROTATE, READ OUT. SINGLE CODE EACH STATEMENT

A great

deal

A fair

amount

A little

Not very

much

Not at

all

Don’t

know

N/A

A. A desire to reduce my impact on the environment 01 02 03 04 05 06

B. Food shortages elsewhere in the world 01 02 03 04 05 06

C. The possibility of saving money 01 02 03 04 05 06

D. Wanting to manage my home efficiently 01 02 03 04 05 06

E. Feelings of guilt when I throw food away that could have been eaten

01 02 03 04 05 06

F. Eating the healthiest diet possible 01 02 03 04 05 06

G. Getting my kids to eat a healthier diet 01 02 03 04 05 06 07

Q28. In the last year, have you seen or heard anything about the amount of food that is thrown away or encouraging us to cut this down? SINGLE CODE

Yes – Go to Q29

No – Go to Q30

Don’t know/can’t remember – Go to Q30 ASK ALLQ29.Where did you see or hear this? ALLOW MULTICODING. READ OUT

TV programme

TV news

TV advert

Newspaper/magazine

Supermarket / shop

Radio programme

Radio news

Radio advert

Social online: community / friends / networks (FaceBook, Twitter, blogs)

Online advert

Internet other

Billboard / outdoor sign / poster

Council publication

Leaflet

Friend / colleague / family member

At an event

At a school


Let’s get cooking club / cookery workshop

iPhone / android application

other (specify)

Don’t know / can’t remember Q30. Please state whether you think the following statements are true or false. READ OUT, ROTATE. SINGLE CODE EACH

True False D/K

A. The average family could save around £50 a month, if they avoided having to throw edible food away

01 02 03

B. Buying food on offer (e.g. buy one get one free; two for £2) leads to more food being thrown away

01 02 03

G. Packaging waste is a worse environmental problem than food waste 01 02 03

PROFILE / DEMOGRAPHICS

Q32. Which of the following best describes your home? SINGLE CODE

Semi-detached house

Terraced house

Detached house

Flat/maisonette

Other Q33. Which of the following best describes your home ownership status? SINGLE CODE

Privately owned

Privately rented

Rented from local authority / housing association

Other

Don’t know

Q34. Do you have use of a garden? SINGLE CODE

Yes, sole use

Yes, shared use

No Q35. Which of the following best describes you? SINGLE CODE

Male, 18-24 years

Male, 25-34 years

Male, 35-44 years

Male, 45-54 years

Male, 55-64 years

Male, 65 years & older

Female, 18-24 years

Female, 25-34 years

Female, 35-44 years

Female, 45-54 years

Female, 55-64 years

Female, 65 years & older Q36. Including yourself, how many people live in your household? SINGLE CODE

1

2

3

4

5

6+


Q37. Do you have children aged 15 years or under living in your household? SINGLE CODE

Yes – Go to Q38

No – Go to Q39 If Q37=Yes ASK: Q38. How many children are there in the following age bands? WRITE IN

0 to 4 years:

5 to 10 years:

11 to 15 years: ASK ALL Q39. What is the job status of the main earner in the household? SINGLE CODE

Full time- Go to Q40

Part time – Go to Q40

Self-employed – Go to Q40

Unpaid work (carer/charity) – Go to Q41

Housewife or student (check they are the main earner) – Go to Q41

Unemployed (looking for work) – Go to Q41

Long term sick / disabled – Go to Q41

Other not working – Go to Q41

Retired – Go to Q40

Q40. What is (or was) the type of work or job title of the main earner? WRITE IN

ASK ALL Q41. Which of the following best describes your ethnic group? SINGLE CODE

White British

White other

Asian

Black

Mixed

Chines

Other (specify) EXPLAIN WASTE COMPOSITONAL STAGE TO RESPONDENT; Focus on anonymity and confidentiality of results

Respondent Name

LANDLINE inc code

MOBILE

EMAIL

House no/name, ROAD

Town

Area

POST CODE

Local authority Harrow 01 Hounslow 02 Richmond-u-Thames 03

THANK AND COMPLETE HARD COPY DECLARATION: If the respondent has any queries at all, ring our freephone support line on 0800 077 8427 (MRS verification number 0500 39 69 99)


Appendix D: Post-Campaign Questionnaire

INTRODUCTION - Provide letter on WRAP headed paper. Speak to person interviewed in pre-campaign fieldwork. If a new household, speak to the

person with responsibility for dealing with the household’s waste and recycling

VERIFICATION

{INTRODUCTION (& WRAP headed explanatory letter)}

QA. Researcher Name. WRITE IN

QB. Local Authority. SINGLE CODE

Harrow 01

Hounslow 02

Richmond-u-Thames 03

QC. DATA REF. WRITE IN

QD. Did household take part in Wave 1? SINGLE CODE (NB Priority is Code 01)

Yes, same respondent in compositional analysis 01

Yes, same respondent, interviewed only 02

Yes, but someone else in household is now responding 03 Ask if original respondent is available; if not continue

No, new household now in property 04

No, new household (other reason, explain) 05_______________

HOUSEHOLD SHOPPING BEHAVIOUR

Q1. How responsible are you for food shopping in your house?

Q2. And how responsible are you for the preparation and cooking of food in your house?

Q1 shopping Q2 Cooking

I have responsibility for all or most of it 01 01

I have responsibility for about half of it 02 02

I have responsibility for less than half of it 03 03

I’m not responsible for any of it 04 04

Q3. Which of these statements best describes your food shopping habits? READ OUT. SINGLE CODE

I buy almost all my food in a main shop. 01 Q5

I buy some food in a main shop and some in “top-up” shops. 02 Q5

I mostly buy food in smaller “top-up” shops. 03 Q4

Q4. If do mainly top-up shops at Q3 ASK: What is the reason for not doing a main shop? DO NOT READ OUT. MULTIPLE CODING ALLOWED

No transportation to do a big shop 01

Prefer to buy foods for meals on daily basis 02

Prefer to visit small or specialist shops 03

No regular pattern for eating meals/irregular working pattern/absence from home 04

Prefer to buy food fresh regularly 05

Prefer to decide what to eat on the day 06

Visit shop on way home so convenient to do this 07

No storage space for big shop 08

Live alone so don’t need a lot 09

To minimise amount of food that goes to waste 10

Have always done this 11

Other (specify) 12___________________________

ON COMPLETION OF Q4 Q9

Q5. If do main shop at Q3 ASK: Which of these statements best describes how often you do your main shop? READ OUT. SINGLE CODE

I do a main shop more than once a week 01

I do a main shop about once a week 02


I do a main shop about once a fortnight 03

I do a main shop about once a month 04

Other (specify) 05___________________________________________

Q6. If do a main shop at Q3 ASK Please think about the last time you did a main grocery shop in a supermarket, grocery store or on-line.

Before that particular shop, did you check what you already had at home for any of the following (if you don’t buy the item let me

know)? READ OUT FOOD ITEMS, SINGLE CODE EACH ITEM.

ITEM YES NO Don’t know/can’t remember I don’t buy this food

A. Fruit 01 02 03 04

B. Vegetables 01 02 03 04

C. Bread 01 02 03 04

D. Fresh meat 01 02 03 04

E. Fresh fish 01 02 03 04

F. Milk 01 02 03 04

G. Ready meals 01 02 03 04

H. Tinned or dried food 01 02 03 04

I. Frozen food 01 02 03 04

J. Salads/leaves 01 02 03 04

Q7. If do a main shop at Q3 ASK: Still thinking about the last time you did a main grocery shop, which of the following describe what you

did beforehand? READ OUT. ALLOW MULTCODING.

I kept a “running list” during the week of things I needed to buy 01

I made a list to take to the shop with me 02

I had a very clear list in my head 03

I had some idea of the kind of things I wanted to buy 04

I shop online and I used ‘my favourites’ to remind me what to buy 05

None of the above 06

Don’t know / can’t remember 07

Q8. If do a main shop at Q3 ASK: Still thinking about the last time you did a main grocery shop which of the following best describes what

you did in the shop? READ OUT. ALLOW MULTCODING {single code sets (01/02/03) and (04/05)}

I bought everything on my list OR 01

I bought most things on my list OR 02

I bought some things on my list OR 03

I bought some extra items not on my list OR 04

I bought quite a lot of extra items not on my list 05

I mostly decided what to buy as I did the shopping 06

I usually buy the same things each week 07

Don’t know / Can’t Remember 08

FOOD STORAGE AND DISPOSAL

Q9. ASK ALL Excluding food that was frozen when you bought it, which of the following items have you put into the freezer IN THE

PAST WEEK? READ OUT. ALLOW MULTICODING

UNCOOKED fresh meat or fish 01

Leftover COOKED meat or fish 02

An unfrozen ready-meal 03

Fresh bakery products 04

Any foods at/near their use by date 05

Fresh milk 06

Homemade meals 07

Other items 08

Nothing 09

Do not have freezer 10

Can’t remember / Don’t know 11


Q10 and Q11. I’d like you to think about the last time you opened a pack of CHEESE / SLICED MEAT. How did you store these after

opening? ALLOW MULTCODING

Q10. Cheese Q11. Sliced meat

In the original packaging 01 01

In a plastic bag (e.g. sandwich or freezer bag) 02 02

In a plastic box (e.g. Tupperware) 03 03

Wrapped in clingfilm or foil 04 04

Other form of wrapping or packaging 05 05

With no wrapping 06 06

All eaten on first opening 07 07

I don’t eat this food 08 08

Don’t know / not applicable 09 09

Q12.I’d like you to think about the last time you went food shopping and purchased FRESH APPLES. When you returned home, where did

you store them? ALLOW MULTCODING

• In a fruit bowl 01

• In a cupboard 02

• On shelf 03

• On worktop 04

• In fridge 05

• Other 06

• Don’t know / can’t remember 07

• Don’t buy / store fresh apples 08

Q13. And thinking about the last time you went food shopping and purchased FRESH CARROTS. When you returned home, where did you

store them? ALLOW MULTCODING

• In a fruit bowl 01

• In a cupboard 02

• On shelf 03

• On worktop 04

• In fridge 05

• Other 06

• Don’t know / can’t remember 07

• Don’t buy / store fresh carrots 08

Q14. To what extent do you decide what you are going to eat for main meals in advance? READ OUT. SINGLE CODE

I know what almost all of the main meals will be for the next week 01

I know what most of the main meals will be for the next week 02

I know what a few of the main meals will be for the next week 03

I usually decide on the day 04

Q15.Thinking about the last time you had leftovers or made more food than was needed, what happened to those leftovers? ALLOW

MULTCODING

Used as part of another meal 01

Used as a meal in themselves 02

Didn’t get used and were thrown away 03

Fed to animals 04

Still being stored 05

Other specify 06 ____________________________________________________

Don’t know / can’t remember 07

Don’t have leftovers 08

Q16. Please think back to the last time you cooked a meal based on RICE. At the end of the meal did you have uneaten rice left over?

SINGLE CODE Yes, deliberately cooked too much for another meal 01 Yes, unintentionally cooked too much 02 No, none left over 03 Don’t know / can’t remember 04


I don’t cook rice 05

Q17. Now think back to the last time you cooked a meal based on PASTA. At the end of the meal did you have uneaten pasta left over?

SINGLE CODE Yes, deliberately cooked too much for another meal 01 Yes, unintentionally cooked too much 02 No, none left over 03 Don’t know / can’t remember 04 I don’t cook pasta 05

Q18.Over the LAST WEEK, have you thrown any of the following away because the date on the packaging has expired? READ OUT. SINGLE

CODE

YES NO Don’t know Do not buy

A. Fresh meats 01 02 03 04

B. Precooked meats (e.g. corned beef, ham) 01 02 03 04

C. Milk 01 02 03 04

D. Yoghurts 01 02 03 04

E. Ready meals 01 02 03 04

F. Fruit juices 01 02 03 04

G. Bread or other bakery items 01 02 03 04

H. Fresh fruit 01 02 03 04

I. Vegetables 01 02 03 04

J. Frozen items 01 02 03 04

K. Any other items? 01 02 03

Q19. Over the LAST WEEK, how much of the following foods have you thrown away (in a compost bin, ordinary bin, council collection,

down the sink or fed to pets etc.)? READ OUT: ROTATE STATEMENTS, SINGLECODE EACH STATEMENT

Quite a

lot

A reasonable

amount

Some A small

amount

Hardly

any

None Don’t

eat this

A. Fruit 01 02 03 04 05 06 07

B. Vegetables or salad 01 02 03 04 05 06 07

C. Bread and cakes 01 02 03 04 05 06 07

D. Raw or home cooked meat & fish 01 02 03 04 05 06 07

E. Cheese and yoghurt 01 02 03 04 05 06 07

F. Milk and fruit juices 01 02 03 04 05 06 07

G. Ready meals or convenience foods 01 02 03 04 05 06 07

H. Homemade meals 01 02 03 04 05 06 07

I. Parts of food not normally eaten (e.g. peelings, bones)

01 02 03 04 05 06 07

J. Food you cooked or prepared too much of but didn’t serve up

01 02 03 04 05 06 07

K. Food left on the plate after the meal 01 02 03 04 05 06 07

L. Foods bought but not used at all (e.g. unopened packs; whole fruit)

01 02 03 04 05 06 07

M. Food from packs that have been opened but not finished (e.g. slices of ham, bread rolls, cooking sauce etc.)

01 02 03 04 05 06 07

N. Food that’s gone off or mouldy 01 02 03 04 05 06 07

O. Food that’s gone past its use by date 01 02 03 04 05 06 07

Q20. Thinking about the different types of food discussed in the previous question, how much uneaten food, overall, would you say you

generally end up throwing away? SINGLE CODE

Quite a lot 01

A reasonable amount 02

Some 03

A small amount 04

Hardly any 05

None 06

Don’t know 07


Q21. Thinking about when you have thrown food away, how is it disposed of in your home? ALLOW MULTICODING; PROMPT

In the general refuse bin 01

Home compost bin 02

Food waste digester 03

Home wormery 04

Council food waste collection 05

Down the sink/drain 06

Fed to animals (pets, birds) 07

Other (do not specify) 08

Don’t know 09

LFHW CAMPAIGN

Q22. In the LAST YEAR, have you seen or heard anything about the amount of food that is thrown away or encouraging us to cut this

down? SINGLE CODE

Yes 01 Q23

No 02 Q24

DK/can’t remember 03 Q24

Q23. What did you see or hear about the amount of food thrown away or encouraging us to cut this down? DO NOT READ OUT.

MULTIPLE CODING ALLOWED

Food recipe postcard 01

Fact card (facts on storage, portion sizes, date labels etc.) 02

Food lovers’ card (card with picture of toast, cheese, apple, milk) 03

Food Lovers’ leaflet 04

Radio advert on LBC 05

Poster on tube/underground 06

Poster/advert on bus 07

Let’s Get Cooking Clubs / Volunteer training 08

Road show 09

Alternative Valentine’s /Food Waste banquet 10

Advertorial in newspaper 11

Newspaper advert in the Metro 12

TV programme, news or advert 13

Supermarket / shop 14

Social online: community/friends/networks (Facebook, Twitter, Blogs) 15

Online/internet advert 16

Friend / colleague / family member 17

At a school 18

Council publication 19

iPhone/android application 20

Other (specify) 21____________________________

DK/can’t remember 22

Q24. I am going to show you some images and advertising from the recent West London campaign. Please tell me if you recognise or

recall any of them? SHOW /PLAY MATERIAL ON IPAD. SINGLE CODE EACH

ACTIVITY IMAGE shown Definitely

seen/heard

Definitely NOT

seen/heard

Unsure COMMENTS

A. Food recipe cards

1 2 3

B. Fact cards

1 2 3

C. Food lovers’ cards

1 2 3

D. Food Lovers’ leaflet

1 2 3

E. Radio advert on LBC PLAY audio 1 2 3

IF CODE 21 or SKIPPED at Q23 AND CODE 02 OR 03 for all A-E at Q24) Q32B


Q25. Has what you saw or heard from the campaign had an impact on what you do? SINGLE CODE

Yes, 01 Q27

No 02 Q26

Don’t know 03 Q31

Q26. Why do you say the campaign has not had an impact? DO NOT READ OUT. WRITE IN THEN CODE - MULTIPLE CODING ALLOWED

I already shop smart 01

I already store foods so they last longest 02

I already use leftovers/random ingredients 03

Measure ingredients / portion control 04

I do not have any/already minimise food waste 05

Not yet had time to implement new behaviours 06

Just made me more aware of the issues 07

Don’t believe the campaign messages 08

Don’t want to change behaviours/ other priorities 09

Other (specify) 10_________________

IF CODE 06 AT Q26 Q27, OTHERWISE Q32B

Q27. What element of the campaign has been most influential to you? WRITE IN

Q28. What do you now do (or do you intend to do) because of what you saw or heard from the campaign? DO NOT READ OUT. WRITE IN

THEN CODE - MULTIPLE CODING ALLOWED

Shop more smartly 01

Store foods better so they last longest 02

Use up leftovers/random ingredients 03

Measure ingredients / portion control 04

Better use of food dates 05

Dispose of food waste better (compost) 06

Discuss food waste with friends / family / colleagues 07

Other (specify) 08____________________

Q29. Do you think that you are wasting less food as a result of the changes you have made? SINGLE CODE

Yes 01

No 02

Don’t know 03

Q30. Do you think that you are saving money as a result of the changes you have made? SINGLE CODE

Yes 01 Q31

No 02 Q32B

Don’t know 03 Q32B

Q31. Approximately how much money do you think your household is saving per month because of the changes you have made? WRITE

IN or SINGLE CODE

£________________

Don’t know 01

Q32A. Approximately how much money do you think your household could save on average each month if you took further action to

avoid throwing away uneaten food? INCLUDE ANY ESTIMATED SAVINGS FOR ACTION ALREADY TAKEN TO GIVE A TOTAL ESTIMATED £

SAVINGS PER MONTH. WRITE IN or SINGLE CODE

£________________

I could not take any further action (explain) 01___________________

Don’t know how much 02

ON COMPLETION OF Q32A Q33


Q32B. Approximately how much money do you think your household could save on average each month if you avoided throwing away

uneaten food? WRITE IN or SINGLE CODE

£________________

Would not be able to avoid throwing food away (explain) 01_____________________________

Don’t know how much 02

Q33. ASK ALL Please state whether you think the following statement is true or false. READ OUT. SINGLE CODE

“The average family could save around £50 a month, if they avoided having to throw edible food away”

True 01

False 02

Don’t know 03

IF CODE 01 or 02 at QD (Wave 1 participant)Q44; OTHERWISE Q34

PROFILE / DEMOGRAPHICS

These questions are to help identify how different households behave differently regarding food waste issues. Your responses will not be

used to identify you at all

Q34. Which of the following best describes your home? SINGLE CODE

Semi-detached house 01

Terraced house 02

Detached house 03

Flat/maisonette 04

Other 05

Q35. Which of the following best describes your home ownership status? SINGLE CODE

Privately owned 01

Privately rented 02

Rented from local authority / housing association 03

Other 04

Don’t know 05

Q36. Do you have use of a garden? SINGLE CODE

Yes, sole use 01

Yes, shared use 02

No 03

Q37. Which of the following best describes you? SINGLE CODE

Male, 18-24 years 01





Male, 65 years+ 06

Female, 18-24 years 07





Female, 65 years+ 12

Q38. INCLUDING YOURSELF, how many people live in your household? SINGLE CODE

One person 01

Two people 02

Three people 03

Four people 04

Five people 05

Six or more 06


Q39. Do you have children aged 15 years or under living in your household? SINGLE CODE

Yes 01 Q39

No 02 Q40

Q40. How many children are there in the following age bands? WRITE IN

0 to 4 years:_____ 5 to 10 years:_____ 11 to 15 years: _____

Q41. ASK ALL What is the job status of the main earner in the household? SINGLE CODE

Full time 01 Q42

Part time 02 Q42

Self-employed 03 Q42

Unpaid work (carer/charity) 04 Q43

Housewife or student (main earner?) 05 Q43

Unemployed (looking for work) 06 Q43

Long term sick / disabled 07 Q43

Other not working 08 Q43

Retired 09 Q42

Q42. If EMPLOYED or RETIRED at Q41 ASK: What is (or was) the type of work or job title of the main earner? WRITE IN

Q43. ASK ALL Which of the following best describes your ethnic group? SINGLE CODE

White British 01

White other 02

Asian 03

Black 04

Mixed 05

Chinese 06

Other (specify) 07 ____________________

WASTE ANALYSIS & INFORMED CONSENT

INFORMATION ON WASTE COMPOSITONAL STAGE & £10 VOUCHER INCENTIVE

Q44. Are you willing for your household to be considered for this part of the research? (NB can opt out at any time)

SINGLE CODE

Yes 01 Write in declaration number: _______________

No 02

Respondent Title Mr Mrs Miss Ms Dr Sir Other (write in)

Respondent First name Respondent Surname

LANDLINE inc code 0 MOBILE 0

EMAIL

House no/name Road

Town Area

POST CODE

Researcher name

Date

If the respondent has any queries at all, freephone support 0800 077 8427; MRS verification number 0500 39 69 99


Appendix E: Waste Composition Sort

Sheet

ID code

Date

Collection area

What is being sorted

kg including packaging kg excluding packaging

Avoidable

Raw fruit and vegetable matter - Whole,

unopened in packaging

Raw fruit and vegetable matter -

Removed from opened packaging or loose

Raw meat and fish - Whole, unopened in

packaging

Raw meat and fish -Removed from

opened packaging or loose

Cooked or prepared food - Whole,

unopened in packaging

Cooked or prepared food - Removed from

opened packaging or loose

Possibly avoidable food all

Non-avoidable food all

Unidentifiable food

All other waste

Comments

List food items that were not readily classifiable

Description Weight

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