Profiling users and non-users of meal delivery services in Belgium using latent class analysis

BACKGROUND: Ready-to-eat meal delivery services have become increasingly popular in recent years, with potential detrimental health implications as the majority of food promoted and sold is energy-dense and nutrient-poor. However, limited research has examined who uses these services and why. This study explores the profiles of different users and non-users of meal delivery services and further describes the socio-demographic and health characteristics of these profiles. METHODS: Data were from 1086 adults who completed the online 2024 Meal Delivery Survey conducted in the Flanders and Brussels regions of Belgium. Users of meal delivery services reported on usage indicators (e.g., valuing fast delivery, ordering to avoid traffic) and non-users reported on reasons for non-use (e.g., lacking trust in meal hygiene, finding it bad for the environment). Latent class analysis categorised users based on patterns of indicator endorsement. Amongst non-users, reasons for non-use were examined descriptively for both former users and never users. Socio-demographic and health characteristics were compared across profiles. RESULTS: Over 66% of the sample (n = 720) were users and 34% (n = 366) non-users. Latent class analysis identified two user profiles. Efficiency-focused users (48% of user sample) solely prioritised fast and affordable service. Variety- and convenience-driven users (52% of user sample) endorsed a wider range of indicators, including the ability to try different cuisines, avoid supermarkets, and have more leisure time. The latter group included more frequent users. Amongst non-users, both former users (52% of non-user sample) and never users (48% of non-user sample) most commonly reported preferences for in-store food shopping and home cooking as reasons why they did not order meals for delivery. Profiles differed in socio-demographic and health characteristics. For example, variety- and convenience-driven users reported poorer health than efficiency-focused users. Non-users (former and never) were older than users, with never users having the oldest age profile. CONCLUSIONS: This study provides a better understanding of determinants of use and non-use of meal delivery services, informing public health action aimed at improving food behaviours and reducing the burden of diet-related diseases. Results can support the development of targeted interventions addressing main drivers of meal delivery service use.