Evaluating the Knowledge, Attitudes and Understanding of Low-fat Nutrition Labels/Claims among University Students
Abstract
Background: Studies have shown that Traffic Light (TL) nutrition labels can be effective in directing consumers towards healthier food choices. While the self-reported understanding of labels is relatively high (>50%), it is not reflective of its actual use. The study assessed the knowledge, attitudes, self-reported and practical understanding of TL labels and low-fat claims on food products; among university students due to the limited literature available on this demographic.
Methodology: The cross-sectional study, included a questionnaire comprising of 11 forced-choice and free-response questions (n=111) and a sensory experiment (n=43) to investigate if the taste of low-fat products affects consumer preference. Chi-square analysis, independent t-tests and statistical tables were used during data analysis.
Results: Of the 97.3% respondents who were aware of TL labels, 93.7% agreed that it can support consumers in making healthier food choices and aid in the reduction of diet-related diseases (p=0.026). While the self-reported rate for label use was 76.9%, (Females: 50%; Males: 26.9%) only 41.4% were able to interpret the TL labels correctly. Similarly, 51.3% of the participants perceived that low-fat foods did not have fewer calories; with 18.9% stating that it was due to the sugar-fat replacement. Findings from the sensory experiment indicated that the presence of nutrition information does not alter consumers’ preference for food products.
Conclusion: Low levels of practical understanding on TL labels indicated that consumers may not effectively use the labels, especially when a low-fat claim is made; masking the overall credibility of the nutrition information provided to facilitate a healthy dietary choice.
The shift in dietary patterns since the 1980s is one of the biggest influencers of the rising rates in overweight and obesity due to increased calorie consumption worldwide (WHO 2015). The prevalence of overweight and obesity has doubled since the 1980s globally (Swinburn et al., 2011; Ng et al., 2014; PHE, 2016); with 1.9 billion (39%) adults aged 18 and above being overweight, and 600 million (13%) classed as obese in 2014 (WHO, 2015). The increased availability of ultra-processed foods which are formulated with the addition of additives and preservatives apart from salt, sugar, fats and oils to imitate the organoleptic properties of a minimally processed food product (Martínez-Steele et al., 2016) has led to the increased consumption rate; accounting for more than 50% of the total calorie intake in high-income countries (Monteiro et al., 2013). The United Kingdom (UK) is ranked eighth among 34 Organisation for Economic Cooperation Development (OECD) countries for its overweight and obesity prevalence (OECD, 2016).
Although the prevalence trend is lower than in the US, the rate of growth is 72% higher in the UK compared to a 46% increase in the US, since the 1980s. This is potentially due to the growth in affluence as a nation and the increased employment specifically among women; who work outside of home, which in turn negatively influences the time spent for home activities, such as food preparation (Johnson, 2012). Also, the wide availability of energy dense and convenience foods (Johnson et al., 2015; Atay & Bereket; 2016), promotes excessive caloric intake (Musingarimi, 2008) contributing to a significant clinical and economic burden to the nation. If the current trends continue to persist, 3.3 billion (57.8%) of the global adult population will be overweight or obese (Kelly et al., 2008) while an additional 11 million adults in the UK will become obese by 2030 (Wang et al., 2011). With respect to the economic burden, it was estimated that the National Health Service (NHS) in England spent £5.1 billion in 2014/2015 on overweight and obesity-related ill health treatments (Scarborough et al., 2011; PHE; 2016) and if the present trends continue, it would cost the NHS approximately, £22.9 billion a year by 2050 to treat obesity and its co-morbidities in the UK (Johnson et al., 2015).
1.1 Nutrition Labelling as an Intervention Tool
Based on the data collected by the National Diet Nutrition Survey (NDNS) in 2012, the average diet of a British adult exceeds the recommended dietary intakes of non-milk extrinsic sugars, salt and fats (NOO, 2012). This is of great concern due to the linear relationship between the increased consumption of convenience foods and the risks of non-communicable diseases (NCDs) such as cardiovascular disease (CVD), diabetes and obesity (Jones & Richardson, 2007). With obesity and its co-morbidities being a multi-faceted issue, governments and other regulatory bodies are developing a range of policy interventions to tackle the epidemic. Some of which include, public health messages to reduce the intake of limiting nutrients (WHO, 2002) as well as the display of nutrition labels on pre-packaged food products to promote healthy eating habits among the population (Cowburn & Stockly, 2005).
Nutrition labelling is a cost-effective strategy (Cecchini et al., 2011) that facilitates the consumer to make informed dietary choices. It is seen as a credible source of information and an education tool that can help influence consumer behaviour at the point of purchase (Kyle & Thomas, 2014). Although nutrition labelling on pre-packaged food products used to be voluntary in the European region (Campos et al., 2011), and is only mandated if a nutrition claim has been made on the product (Grunet & Wills, 2007); the guideline was modified as of December 2016. All pre-packaged products (excluding exempted products such as teas, flavourings, additives and etc.) require nutrition information to be displayed on the back or the side of the packaging (PHE, 2017), similar to the labelling regulations in the United States and Canada (Campos et al., 2011).
Nutrition information shown on the back-of-pack (BoP), typically contains information on the serving size, energy, protein, fat, saturated fat, carbohydrate, added sugars, fibre, salt, vitamins and minerals (Borgmeier & Westenhoefer, 2009). While its purpose is to aid consumers in the purchase decision of the product, research has shown that BoP labels can be confusing due to the numbers and terminologies used (Cowburn & Stockley, 2005); and easily misinterpreted while estimating the nutritional value of the product based on the portion size to be consumed (Drichoutis et al., 2006; Heike & Taylor, 2012; Miller & Cassady, 2015). Due to the reported difficulties in interpreting the quantitative information on the BoP labels (Baltas, 2001; Drichoutis et al., 2006; Campos et al., 2011), the efficacy of nutrition labels influencing consumer purchase behaviours was compromised. As a result, a simple, systematic and clearer format like a graphic representation (Campos et al., 2011) that allows a quick assessment of the product was required, to communicate the same information to the consumers (Lynam et al., 2011).
Hence, simplified nutrition labels were developed by the respective regulatory bodies, food manufacturers, retailers and not-for-profit organisations to supplement the existing BoP information, on food products (Feunekes et al., 2007; Borgmeier & Westenhoefer, 2009; Tarabella & Voinea, 2013). The front-of-pack (FoP) labels can be added to pre-packaged food products on a voluntary basis in the European region, to further support consumers with the decision-making process. A FoP label provides a summarised version of nutrition information found on the BoP by interpreting the levels of energy and the key limiting nutrients such as fat, saturated fat, sugars and salt (Feunekes et al., 2007; Talati et al., 2016); providing the consumer with concise details on the overall healthiness of the product (Feunekes et al., 2007).
As FoP labels require a lower amount of time and cognitive effort to process the nutrition information provided on a food product; it can better guide consumers with the food purchase decisions (Feunekes et al., 2007) especially since there has been evidence on the limited opportunities consumers have in a supermarket environment to process detailed BoP labels and instead, glance at the nutrition information at the point of purchase (Higginson et al., 2002).
Various types of FoP labelling systems provide either summary-based or nutrient specific information (Wartella et al., 2010) in the form of simplistic health logos or detailed labels highlighting the key nutrients of the food product.
Interpretive logos placed on the front of a food product can enable the quick and easy identification of foods based on its overall nutritive value (Feunekes et al., 2007; Wartella et al., 2010), reducing the level of cognitive skills required to analyse the information (Grunert et al., 2010). The health logos are applied to food products that meet specific nutrient requirements based on the product categories. Some examples of the health logos include the American Heart Association Heart Check which is applied to heart-healthy products, USA’s Smart Spot, Singapore’s Healthier Choice Symbol, Australia/NZ’s “Pick the Tick” symbol, Swedish Food Administration Keyhole and the Choices logo that are seen on foods that meet the respective nutrient requirements for selective nutrients such as trans-fat, saturated fat, fat, salt, sugars and fibre (Young & Swinburn., 2002; Wartella et al., 2010; Roodenburg et al., 2011; HPB, 2017; Choices, n.d.)
The guideline daily amounts (GDA) labelling system is one of two types of detailed FOP systems voluntarily adopted in the European region. Developed by the Institute of Grocery Distribution (IGD) in the UK, the GDA labels act as a guide for consumers showing the amount of energy and nutrients present in a portion size of a food product, as a percentage, based on the recommended energy requirement for a healthy adult of 2000 kilocalories a day (Borgmeier & Westenhoefer, 2009; Tarabella & Voinea, 2013).
The aim of GDA labels is to provide nutrition information in a clear and an objective manner to allow the consumer to make an informed food choice. Although, the GDA system has received considerable attention on its user-friendliness and the increased level of consumer understanding of reading such labels in the UK and Sweden (Grunert et al., 2010), it has been reported that the GDA system may not be appropriate for all consumers; specifically those with low levels of education. As the system uses a quantitative approach in displaying the nutrition information, it requires consumers to scrutinise the information carefully. Also, as the portion sizes are determined by the manufacturers, the nutritional profile of the product can be adjusted with a smaller portion size, especially for high caloric foods such as crisps and chocolates, altering the consumer’s choice (Tarabella & Voinea, 2013).
Developed by the Food Standards Agency (FSA) in 2006, the Traffic Light (TL) labelling system uses the red, amber and green colour codes to indicate the high, moderate and low amounts of limiting nutrients per portion based on the recommended daily energy intake of a healthy adult (Borgmeier & Westenhoefer, 2009). Apart from influencing healthier food choices, the purpose of the TL system is to help consumers overcome the challenges faced with previous labelling systems (Malam et al., 2009). With its clear and simple approach to influence the consumer’s purchase behaviours, the above system has been recognised and supported by health organisations for its effectiveness and its wide reach to the various target groups, regardless of educational level, age, and sex (Sacks et al., 2009). Furthermore, it is a potential tool to help shape the eating habits of young children and adolescents (Tarabella & Voinea, 2013). Based on the UK FSA and a market study conducted by the European Food Information Council (EUFIC), it was revealed that the TL labelling format was well understood and widely accepted by the population (EUFIC, 2008; Borgmeier & Westenhoefer, 2009).
On the flipside however, TL labels can hinder with the comparison of two similar food products as the labelling system does not have a benchmark criteria on the recommended products and only targets the limiting nutrients; neglecting the presence of other nutrients; such as dietary fibre and protein. Moreover, for dairy products, nutrients such as saturated fat are highlighted in red. This compromises the presence of other positive nutrients such as calcium (Wartella et al., 2010; Tarabella & Voinea, 2013). Apart from that, the representation of the red colour in TL labels led 73% of the UK consumers to believe that the product needs to be avoided, rather than being consumed on occasion (EUFIC, 2008).
Health claims are defined as the written description of scientifically proven health benefits associated with the consumption of a certain food product (i.e. calcium may help improve bone density) (Williams, 2005); while, nutrient claims informs the consumer about the presence or absence of a nutrient (i.e. low in fat/sugars) (Talati et al., 2016). Such claims are added onto the FoPs, to serve the same role as the above mentioned labelling systems- to guide consumers in making better informed food choices (Hung et al., 2017), while also instilling a competitive edge for a product in the food industry.
While health claims are a beneficial tool that provides essential information cues influencing food choice (Heike et al., 2015; Talati et al., 2016), it can mislead consumers due to the positive representation of a product instead of displaying the overall summary of its nutritional value. For instance, a product with a low-fat or a fat-free claim is compensated with considerable quantities of other unhealthy nutrients such as sugar (Talati et al., 2016) to maintain the sensory properties of the original version (Sandrou & Arvanitoyannis, 2000). The lack of clarity on these claims can affect unbiased product evaluations, influencing the consumption of the products in larger quantities as compared to a product without the claim (Faulkner et al., 2014); or lead to a favourable judgement (Saba et al.,2010). Although the claims are intended to support informed decisions towards healthy food choices, a qualitative study conducted in Australia reported that the consumers saw the presence of health and nutrient claims as a marketing gimmick, due to the lack of trust in the food manufacturers (Talati et al., 2016).
The availability and affordability of convenience foods that are high in fat, sugar and salt can be attributed to the poor food purchasing and consumption habits among the younger population group (Plotnikoff et al., 2015), particularly in university students, who are living away from home for the first time (Graham & Laska, 2012). The poor dietary choices adopted during this period are likely to continue throughout their lives (Plotnikoff et al., 2015; Aceijas et al., 2016). Therefore, it is important to facilitate healthy dietary choices through the provision of nutrition information on pre-packaged foods.
The UK has taken the lead in promoting healthier food choices through FOP labels (Grunert et al., 2010) compared to its European counterparts, with 82% of the food products displaying the FoP labels (Draper et al., 2011). With a variety of FoP labelling systems being adopted by the food industry, studies have been conducted to investigate if the presence of FoP labels has indeed influenced consumers’ dietary choices.
Based on a systematic review and meta-analysis conducted by Cecchini and Warin (2016), it was noted that the traffic light labelling format can be significantly effective in influencing consumers to make healthier food choices. This was also observed in several other studies conducted in the European region, evaluating the use and understanding of nutrition labels among consumers. The display of nutrition labels has received widespread attention (Grunert & Wills; 2007) among consumers, particularly due to the increased interest in health and diet issues (Borgmeier & Westenhoefer, 2009). Of the six different label formats evaluated; including a healthier choice tick, health protection factor, stars, smileys, multiple traffic light system and the wheel of health, the TL system scored the highest among other formats due to its credibility and understanding (Feunekes et al., 2007). Although there was a high awareness rate (81%) of TL labels among UK consumers (EUFIC, 2008), the understanding level was slightly lower, ranging from 58% to 71% (Malam et al., 2009).
Although the understanding of nutrition information is relatively high in the UK, the level of understanding does not equate to the usage level. Often the self-reported rates of label use is generally high (Cowburn & Stockley, 2015) and above 50% (Campos et al., 2011). However, consumers reportedly had difficulties interpreting the quantitative information found on the labels (Baltas, 2001; Mhurchu & Gorton, 2007). Moreover, several other studies conducted by EUFIC (2008), revealed that only 25% of the UK consumers look for nutrition information in a supermarket environment (Tarabella & Voinea, 2013) and analyse the nutrition label of a food product for about 25 seconds (EUFIC, 2008); focusing on calorie, fat, saturated fat, sugar and salt content (Grunert et al., 2010).
Prevalence of label use in relation to demographic factors changes with age, gender, education and income level, irrespective of the label formats. For instance, in the United States, older participants referred to nutrition labels as source of information, as opposed to the younger population due to the increased interest, in health and diet issues (Worsley, 2003; Borgmeier & Westenhoefer, 2009). Similarly, Females had a higher tendency to refer to nutrition labels than males (Misra, 2007; Campos et al., 2011) influencing their dietary choice. Similarly, this was also observed in studies involving university students. The knowledge, attitudes and understanding about diet-disease relationship was significantly higher in females than males at a 99% confidence level (Rasberry et al., 2007; Cooke & Papadaki, 2014). A linear relationship with regards to the level of education was also reported in the literature (Worsley, 2003; Satia et al., 2005; Hess et al., 2005; Campos et al., 2011).
Apart from understanding the nutrition information displayed on the food product, the level of motivation to make use of the label is essential to help steer consumers towards healthier food choices (Grunert et al. 2010). Studies have identified a range of contributing factors for increased label use among consumers. Grocery shopping habits is the most common influencer for label use. However, this is highly reliant on the time spent reviewing the product (Jordan Lin et al., 2004) Furthermore, the use of labels can be positively influenced with nutrition education, weight control, knowledge of the diet-disease relationship and diagnosis of disease (Rasberry et al., 2007; Smith et al., 2007; Campos et al., 2011). Similarly, consumers who are concerned with the dietary recommendations and nutritional quality of food had reported a higher usage of nutrition labels (Krystallis & Ness, 2004). However, the sensory properties of the food product was noted as an important attribute in the decision making process and can override the analysis of the labels before the point of purchase, in some studies (Jensen et al., 1996; Nagya et al., 1998; Nagya, 2000; Grunert & Wills, 2007; Borgmeier & Westenhoefer, 2009). This was further supported in the research conducted by Godwin et al. (2006) with half of the 160 samples consuming high-calorific products such as crisps, chocolates, pastries and soda without looking at the nutrition labels displayed on the product. While, two other research studies indicated that there was no association between the consumption of hedonic foods and the analysis of nutrition labels (Guthrie et al., 1995; Drichoutis et al., 2005).
According to an online survey conducted at Ulster University, students perceived that the key to being healthy, involved limiting the intakes of total fat, saturated fat and sugar (Tierney et al., 2017). While the display of the TL labels are helpful in the evaluation of a food product for 81% of the participants, the purpose of a nutrient claim is to communicate the relative amount of a specific nutrient in a product. It is also often used as a marketing technique to promote the product over its counterparts (Williams 2005; Miller & Cassady, 2015). The use of health claims to evaluate the healthiness of the product has been under constant scrutiny, due to the likelihood of consumers being misled (Hasler, 2008) to perceive a product to have a better nutritional value than the other; when the product with a claim can potentially be more energy dense than one without the message (Fontaine et al., 2004; Balasubramanian & Cole, 2002). Nutrient claims and labels are platforms that convey the objective and subjective consumption cues to individuals. While objective cues can be information related to the serving size, subjective cues are the presence of nutrient claims and the absence of information on the portion size (Wansink & Chandon, 2006).
In the context of products with low-fat labels, the original intention for its endorsement was to guide consumers towards portion control (Wansink & Huckabee, 2005). On the other hand, the claim can induce a “halo effect” that could influence the consumer to believe that the product is healthy, based on a single-nutrient claim (Hughes et al., 2013; Cecchini & Warin, 2016). Such a perception can drive a consumer towards the overconsumption of an energy dense product (Hedley et al., 2004). The display of a low-fat claim can convince an individual to overindulge on hedonic food products such as chocolates and savoury snacks in the absence of an energy deficit, due to the perceived, lower level of guilt associated with the claim. Furthermore, a one-time binge can contribute to rapid satiation and increase the likelihood of weight gain as a result (Wansink & Chandon, 2006).
This is of great concern, specifically in the younger demographic who are pursuing their tertiary education as previous studies have indicated that substantial weight gain occurs during this phase (Gropper et al., 2012; Fedewa et al., 2014); due to the increased intakes of food that is high in sugar, fats and salt. Moreover, the accessibility and affordability of such foods can have a negative influence on the food purchasing techniques within this target group, (Plotnikoff et al., 2015). Hence, it is vital to guide this population group towards healthier dietary choices, by facilitating informed decision making through the presentation of nutrition information as it is likely to follow through adulthood (Plotnikoff et al., 2015). While, there is a wide availability of literature on the knowledge, attitudes, understanding and use of nutrition labels among the general population and college students, based in the United States and Australia; there is limited literature available on UK university students with respect to this research area. This study will assess the knowledge, attitudes and self-reported understanding of nutrition labels as seen in similar studies; indicating that females had a higher level of nutritional knowledge and made use of nutrition labels more frequently than males (Huang et al., 2004; Misra, 2007; Cooke & Papadaki, 2014; Tierney et al, 2017). In addition, the study will also investigate the actual level of label understanding particularly in relation to low-fat nutrition labels and claims and evaluate if the taste profile of low-fat food products can influence consumer preference.
2.1 Aim
To evaluate the consumer knowledge, attitudes and understanding towards nutrition labels and claims
3.1 Study Design
The study assessed the level of knowledge, attitudes and understanding of low-fat nutrition labels among a sample population of UK university students within Liverpool. A cross-sectional design was used for this study, as similar studies had also utilised this approach to evaluate the level of knowledge, attitudes and understanding of nutrition labels in a specific population (Barker et al., 2003; Rasberry et al., 2007; Hung et al., 2017). The current study comprised of two quantitative components which included a questionnaire (Appendix 1) and a three-part sensory evaluation (Appendix 2; Appendix 3) using regular-fat and low-fat hummus samples, to determine the relationship between variables within the demographic group (Flick, 2015). Data collection for questionnaires was conducted over a one-month period while the sensory experiment was conducted over a two-week period between January and February 2017.
3.1.1 Participants
As the study protocol did not have any ethical conflicts (Appendix 4), it was approved following a preliminary review with no further submission made to the research ethics panel to conduct this research. Participants for both experimental components were recruited at random to prevent research bias (Reis & Judd, 2000), even though the target demographic was pre-determined for this study. Participant recruitment was advertised to students across all faculties in Liverpool John Moores University (LJMU) and University of Liverpool (UoL) using a range of platforms. Interested students (n=111) aged 18 and above, were recruited to complete the questionnaire anonymously, in person (n=31) at LJMU campuses (Avril Robarts and IM Marsh); or online (n=80) using the Bristol Online Survey (BOS) portal- a web-based survey tool used to administer questionnaires such as the above to achieve the outcomes of the research. A link to the online version of the questionnaire was advertised with a synopsis explaining the purpose of the research on the following Facebook pages: LJMU International society, African-Caribbean society and the researcher’s personal Facebook page, which was then subsequently shared and forwarded to individuals through the word of mouth within the target demographic pursuing tertiary education in LJMU or UoL. In addition, a recruitment email (Appendix 5.1) via the university’s electronic mailing system was circulated to students from the school of sports studies, leisure and nutrition which included students from sports sciences and food science and nutrition within LJMU.
Convenience random sampling was also used for the three-part sensory experiment. Participants (n=43) studying at LJMU were chosen based on their availability and willingness to take part in the research. Participants were recruited at LJMU’s IM Marsh campus via the word of mouth of university lecturers, the researcher and through the circulation of a recruitment advertisement (Appendix 5.2) via the university email to sports science and food and nutrition students. Prior to the start of the evaluation, participants were screened for any potential nut allergies. This was ensured through the reading of the participant information sheet (Appendix 6) and the receipt of the signed consent forms (Appendix 7) which was adopted in a similar study conducted by Rasberry et al., 2007, indicating the participants’ approval to take part in the experiment. To maintain anonymity of the participants, the consent forms were separated from the sensory questionnaire. Although 43 participants had taken part in all three parts of the sensory evaluation, only the data of 37 participants were selected for the last stage of the sensory experiment, due to an unexpected experimental discrepancy that nullified the responses of six participants.
3.1.2 Questionnaire
A self-administered questionnaire (Appendix 1) which took about ten minutes to complete was disseminated online and in person to obtain data on the demographic group, the level of knowledge, attitudes, subjective and objective understanding of nutrition labels. The questionnaire design was based on a previously validated questionnaire that looked into the nutrition knowledge in an adult population (Parmenter & Wardle, 1999). A total of 11 forced choice (multiple-choice) and free response questions were included in the questionnaire. The structure of the questions began with demographic characteristics of the participants such as sex, age, education level and the programme of study. This was followed by questions that assessed the knowledge and awareness of Traffic Light (TL) labels; and its relationship to diet and disease. Subjective and objective understanding of TL labels was evaluated using the comparison of nutrition labels of food products from the same product category. While, scenario-based questions were used to determine the preference and attitudes towards food products low-fat nutrition claims among participants.
3.1.3 Sensory Evaluation
The three-part sensory evaluation procedure was conducted at the LJMU Food Academy, located at the IM Marsh campus in Aigburth, Liverpool. All tests were conducted in individual, partitioned booths with white lighting. The evaluation, which required comparative judgements, used a simultaneous sample design (Kemp et al., 2009), which involved participants to evaluate two store-bought hummus samples that varied significantly in fat content based on its taste.
3.1.3.1 Triangle Test
The triangle test was the first of three tests that was conducted, to determine if participants were able to identify the difference between the regular and low fat samples. Six possible sample combinations (ABB, BAA, AAB, BBA, ABA, BAB) were prepared (Kemp et al., 2009; Meilgaard et al., 2016) and randomly presented to the participants in separate plastic cups, labelled with a random three-digit code to avoid bias and inaccuracies (Kemp et al., 2009; Moskowitz et al., 2012) (Appendix 2.2).
The participants were presented with three hummus samples, two of which were of the same fat content. Participants were briefed on the test procedure as they were untrained. Hence, they were told to taste the products in order, from left to right (Meilgaard et al., 2016); drinking water in between each sample to cleanse the palate as observed in the British Standards (1986) for sensory analysis throughout the evaluation procedure. After which, the participants recorded their responses on a score sheet that was provided together with the samples (Appendix 3.1).
3.1.3.2 Paired Preference Test
Following the triangle test, participants were briefed on the second part of the evaluation which required them to select a hummus sample they preferred based on its taste profile. The purpose of the test was to determine if any significant sensory difference existed (Lyon et al. 2012) between the regular and low-fat hummus samples. The samples were blind coded using randomised three-digit numbers and served in two possible combinations (AB, BA) to the participants (Appendix 2.3). Upon tasting both samples, participants were reminded to record their preference on the score sheet provided (Appendix 3.2).
3.1.3.3 Paired Comparison Test
As the final leg of the sensory analysis had the same objective as in the paired preference test, the test procedure remained the same. Participants received the samples they were presented with previously in the same order (Appendix 2.4), to identify the sample they perceived to be lower in fat, based on the analysis of the nutrition information provided; and selected the preferred sample upon assessing the nutrition label. 12 of the 37 participants were given two of the same samples (AA/BB) but were not made aware of the change. This was done to evaluate if the presence of the nutrition label had influenced a different preference as opposed to the former test which was then recorded on a score sheet (Appendix 3.3).
Manual calculations were done for all three parts of the sensory evaluation. For the triangle test, the number of participants who identified the odd sample correctly were counted and compared to the statistical table (Appendix 8), to determine if a difference was present at 5% significance level. Similarly, the greater number of responses was compared against the statistical table (Appendix 9) at the set significance level (α=0.05) for the data obtained through the paired preference and comparison tests to assess if there was difference between the tested hummus samples.
3.2.2 Statistical Analysis
The Statistical Package for the Social Sciences Software (IBM SPSS Statistics Version 23) was used to analyse the data collected through the questionnaires. Responses to the open-ended questions were grouped, coded and quantified for the ease of analysis (Flick, 2015; Tierney et al., 2017). Basic descriptive statistics including means and frequencies were used to analyse the demographic data (Rasberry et al., 2007; Vyth et al., 2010). This was also used alongside chi-squaretests and cross tabulations to determine the relationship between the demographic data and the knowledge, attitudes and understanding of nutrition labels. Based on similar researches conducted in the past, an independent t-test was used to compare the actual understanding of nutrition labels and gender (Marietta et al., 1999; Rasberry et al., 2007). The level of significance was set at 5% for all statistical tests.
4.1 Demographic Characteristics
| Sample Characteristics | No. of Samples (n) | Percentage (%) |
| Sex: |
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