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Abstract
Food choices determine consumers’ dietary and energy intakes, and in turn their risk of obesity and diet-related diseases. Factors affecting food choices are complex, varied, and inter-connected. The aims of this study were to assess the relative importance of four factors influencing food choices (taste, price, healthiness, and convenience) and identify segments of consumers according to their ratings. Australian consumers (n=1,558) aged 18+years completed an online survey assessing a range of factors influencing their food choices, including the perceived importance of taste, price, healthiness, and convenience. Latent profile analysis was undertaken to identify segments, with bivariate analyses then conducted to describe the differences between the derived segments. Overall, taste was reported to be the dominant factor determining food choices (Mean (M)=4.42; SD=0.72; z-score=0.43), followed by price (M=4.19; SD=0.78; z-score=0.15), healthiness (M=4.07; SD=0.82, z-score=0.00), and finally convenience (M=3.79; SD=0.82, z-score=-0.35). However, there were variations in absolute and relative ratings across the four identified segments. Two segments (‘High involvement’ and ‘Taste focused’, together accounting for 53% of the sample) rated taste highest, and the other two segments (‘Moderate involvement’ and ‘Indifferent’, 47% of the sample) rated price highest. Age, gender, residential location, and responsibility for grocery shopping were associated with segment membership. Understanding the dominant drivers of food choices across different consumer segments is useful for the development of tailored nutrition promotion messages and interventions to address obesity and other diet-related diseases.
Introduction
The Australian Dietary Guidelines recommend consuming a wide variety of foods daily from the five main food groups (vegetables, fruit, grain cereals, lean meats and alternatives, and dairy foods and alternatives), and limiting ‘discretionary’ foods containing high levels of saturated fat, added salt, or sugars (National Health and Medical Research Council (NHMRC), 2013). However, few Australians meet these recommendations. <10% of adults eat the recommended five serves of vegetables daily, and discretionary foods contribute more than 35% of adults’ daily energy intakes (Australian Bureau of Statistics, (ABS) 2016). This situation is similar around the world, and increasing numbers of people are consuming suboptimal diets that are inconsistent with dietary guidelines (Haack and Byker, 2014, Raulio et al., 2015, Rodríguez-Rodríguez et al., 2017). Poor dietary patterns and high-energy intake contribute to obesity and a range of other nutrition-related diseases that are significant public health concerns globally (World Health Organization (WHO), 2017).
Achieving a healthy diet and a healthy weight are substantial challenges. Once an individual is overweight or obese, it is very difficult to lose weight or maintain weight loss (Sumithran et al., 2011). This is confounded by a global transition in the food supply to greater availability of highly palatable, cheaper, and energy-dense foods (Crino et al., 2015, Popkin, 2017, Vandevijvere et al., 2015). The heavy promotion of these energy-dense and nutrient-poor foods adversely influences consumers’ food choice decisions (Vukmirovic, 2015). Interventions designed to counteract these forces need to be based on a detailed understanding of the factors that facilitate or hinder healthy food choices.
Among other early research on food choice motives, Steptoe, Pollard, & Wardle (1995) developed the Food Choice Questionnaire that addresses nine factors that potentially influence food decisions: sensory appeal (encompassing appearance, taste, and smell), price, healthiness of the food, convenience (easiness to prepare and availability), mood (comprising mood improvement and stress reduction), natural content, weight control, familiarity, and ethical concern. Of these factors, studies from different countries have consistently identified taste, price, healthiness, and convenience as dominating food choices (Aggarwal et al., 2016, Glanz et al., 1998, Hebden et al., 2015, Prescott et al., 2002, Steptoe et al., 1995). While some differences have been found in how people prioritise these factors, taste is typically ranked as most important, with the other factors varying in their relative subsequent positions (Glanz et al., 1998, Markovina et al., 2015, Onwezen et al., 2012, Prescott et al., 2002, Sautron et al., 2015, Verain et al., 2016). Understanding the different consumer segments that exist in relation to the prioritisation of these food choice factors is important for a wide range of public health policies (Grier & Bryant, 2005). These include policies relating to food advertising regulations, food taxation, reformulation targets, and population nutrition education programs.
Approaches to market segmentation vary according to the criterion variables under investigation (i.e., food choice factors in this instance), the predictor variables selected (e.g., demographic characteristics), and the analytical method used. Many segmentation studies to date investigating food choice factors have focused on specific food products (e.g., Ares and Gámbaro, 2007, Bernués et al., 2003, O’Connor et al., 2006, Realini et al., 2014, Verain et al., 2016), and those that have looked at factors affecting food choice in general have been mainly conducted in Europe (e.g., Honkanen and Frewer, 2009, Kornelis et al., 2010, Milošević et al., 2012, Onwezen et al., 2012). In addition, there is the potential to undertake more comprehensive segmentation analyses by including a broader range of potential explanatory variables. Examples of such variables include health-related special dietary requirements, perceived nutrition knowledge, perceived diet healthiness, and grocery-buying role in the household (James, 2004, Moorman et al., 2004, O’Brien et al., 2014, Shatenstein, 2008, Sobal and Bisogni, 2009, Worsley, 2002).
In terms of analytical methods, most food choice factor segmentation studies to date have used cluster analysis (e.g., Ares and Gámbaro, 2007, Bernués et al., 2003, Honkanen and Frewer, 2009, Milošević et al., 2012, O’Connor et al., 2006, Verain et al., 2016). In recent years, latent profile analysis has emerged as an advanced method that involves classifying individuals into different segments based on a probabilistic model-based approach that describes the distribution of the data after taking uncertainty about segment membership into account. This analysis uses statistical tests selecting the best model so that the choice of the segments is less arbitrary, thereby outperforming the traditional cluster analysis explanatory approach (Fraley and Raftery, 1998, Hagenaars and McCutcheon, 2009, Magidson and Vermunt, 2002). To date, however, few studies have employed this approach in the context of food choice research (exceptions include Kornelis et al., 2010, Realini et al., 2014), and there remains the potential to use this sophisticated analysis method to obtain a deeper understanding of the interplay between different choice factors across different consumer segments.
The present study aimed to assess (a) the relative importance of the food choice factors of taste, price, convenience, and healthiness in determining consumers’ food choices; (b) identify segments of consumers based on these ratings; (c) describe the characteristics of derived segments; and (d) consider the results for the food policy and program implications. This study extends prior food choice segmentation research by investigating across food types, applying a wide range of predictor variables, and using latent profile analysis to identify discrete consumer segments. The results are interpreted in terms of the implications for nutrition policies and programs.
Section snippets
Materials and methods
This study was part of a larger research project assessing the influence of nutrition information and food labelling on Australians’ food choices (Talati et al., 2017). Ethics approval for the project was obtained from the Curtin University Human Research Ethics Committee (approval number: RDHS-11-15) and all participants provided informed consent.
Descriptive statistics
Across the entire sample, taste was rated as the most important determinant of food choice, with a mean score of 4.42 on the 5-point scale (SD=0.72, z-score=0.43). This was followed by price (M=4.19, SD=0.78, z-score=0.15) and healthiness (M=4.07, SD=0.82, z-score=0.00). Convenience was rated lowest (M=3.79, SD=0.82, z-score=-0.35). The z-score differences between the four food choice determinants were significant (p<0.001 for each paired comparison).
Fit statistics
The computed 2-to
Discussion
This study aimed to assess consumers’ relative ratings of the primary factors determining their food choices and identify segments according to these ratings. Among the four identified segments, taste was rated highest for two of the segments and also received an average rating of 4 or more on a 5-point scale for three segments that together comprised 93% of the sample. This finding relating to the importance of taste in driving food choices is consistent with previous studies (Aggarwal et al.,
Conclusion
This study contributes to the growing evidence that taste and price are the most important factors determining consumers’ food choice decisions. Although consideration of food healthiness in consumption decisions is important for preventing nutrition-related chronic health conditions, the findings of the present study show that this factor was rated lower relative to taste and price for the large majority of respondents, regardless of levels of perceived diet healthiness, perceived nutrition
CRediT authorship contribution statement
Liyuwork Mitiku Dana: Conceptualization, Data curation, Formal analysis, Methodology, Writing - original draft, Writing - review & editing. Kathy Chapman: Writing - original draft, Writing - review & editing. Helen Dixon: Funding acquisition, Methodology, Writing - review & editing. Caroline Miller: Funding acquisition, Methodology, Writing - review & editing. Bruce Neal: Funding acquisition, Methodology, Writing - review & editing. Bridget Kelly: Funding acquisition, Methodology, Writing -
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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An 18-country analysis of the effectiveness of five front-of-pack nutrition labels
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Various front-of-pack food labels (FoPLs) are being introduced across the world, and discussion continues about the most effective label formats to improve consumers’ (i) understanding of the relative healthiness of alternative products and (ii) product choices. Of increasing interest is the relative ability of different types of labels to steer consumers away from unhealthy options (aversion) versus steer them towards healthier options (attraction). The aim of this study was to assess aversion and attraction outcomes for five FoPLs (Health Star Rating, Multiple Traffic Lights, Nutri-Score, Reference Intakes, and Warning Label) across 18 countries (n = 18393). Descriptive analyses assessed improvements in consumer understanding and choice outcomes for each label across three different types of food products. Binary logistic regressions were used to compare the relative ability of the labels to improve respondents’ understanding of product healthiness and their product choices, using the industry-developed Reference Intakes as the comparator. Aversion and attraction effects were assessed for each label/food type combination. Across the total sample, the Nutri-Score performed best in terms of both attraction and aversion results for understanding and simulated choice outcomes, followed by the Multiple Traffic Lights. The Reference Intakes exhibited the weakest performance overall, with the Warning Label and Health Star Rating falling in between. The most effective FoPLs featured a colour-coded spectrum design. The results indicate that front-of-pack labels that are effective in guiding consumers towards healthier food products can also be effective in steering them away from unhealthy options.
An increasing number of studies investigate the effect of front-of-pack (FOP) nutrition labels on consumer choice without considering differences in consumer preferences for product attributes. This study used a choice-based conjoint analysis to test consumers' preferences for four product attributes (5 levels of a FOP nutrition label, absence/presence of a nutrition claim, brand (unfamiliar, private label or premium) and 5 levels of price) when they coexist (n=1156). As the consumer preferences showed distinct patterns (multimodality), consumers were subsequently clustered based on how a FOP nutrition label (Nutri-Score) influenced their food choices. Three consumer segments were identified, each valuing the Nutri-Score label differently. The label effectively seems to nudge one segment toward healthier choices (n=456), while in contrast, another segment is unexpectedly steered toward unhealthier food choices by the label (n=343). The third segment is only consistently nudged by the FOP label's extremes (n=357). The segments also differ in their preferences for other product attributes (brand and price), health involvement, and self-reported understanding and use of the Nutri-Score, but not in the measured socio-demographic variables (age, sex, education, social class), dieting or smoking habits. In summary, consumers vary in their food label preferences, and studies that pool consumers may fail to capture these nuances, leading to biased results. This study shows that FOP labels do not steer all consumers toward healthier choices and may even have adverse effects for some. This suggests combining different policies and marketing strategies to reach all consumer segments.
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Concerns over the impact of global meat production and consumption patterns are leading to increasing interest in alternative sources of protein. This study provides new insight into consumers’ attitudes towards different protein products and factors associated with the acceptance of lab-grown chicken and lab-grown beef. We measured and compared 1078 Australian consumers’ beliefs regarding conventionally raised meat (chicken and beef), plant-based meat alternatives and lab-grown meat products across six attributes: health, safety, affordability, eating enjoyment, animal welfare, and environmental friendliness. Beliefs regarding the health and affordability of conventionally raised chicken were statistically highest. For all attributes, beliefs relating to plant-based meat alternatives were more positive than those relating to lab-grown meat, and with respect to animal welfare and environmental friendliness, plant-based products were viewed most positively relative to all products. Despite average negative belief scores for all attributes, except for animal welfare, around one-quarter of consumers still indicated a willingness to consume lab-grown chicken and lab-grown beef. Multinomial logistic regressions were used to explain factors associated with consumers’ willingness to consume lab-grown meat products. Factors associated with willingness to consume the lab-grown meat products were positive beliefs regarding eating experience (enjoyment), safety, animal welfare, and healthiness; familiarity; higher consumption frequency of conventionally raised chicken meat; tertiary education; and younger age. Although lower environmental impact has been proposed as one of the main benefits of lab-grown meat, beliefs regarding environmental friendliness were not significant in either model.
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