# Conjoint analysis of social inequality indicators in diet and physical activity app (non-)users: Representative online surveys in Austria, Germany and Italy

## TL;DR

This study explores how social inequality affects the use of diet and activity apps in Austria, Germany, and Italy.

## Contribution

The study identifies distinct user groups and highlights a digital health divide linked to age, education, income, and employment.

## Key findings

- Four distinct classes of mHealth app users were identified based on socio-demographic factors.
- Younger and more educated individuals are more likely to use health apps.
- Low-income workers and retirees are less likely to use these apps.

## Abstract

Mobile interventions for health promotion (mHealth) are promising behaviour change tools. Yet they are infrequently used, and research suggests that use may be unevenly distributed in the population, potentially widening existing health inequalities.

This study tested for individual and joint associations between socio-demographic characteristics and nutrition and physical activity app use.

Nationally representative samples for Austria, Germany and Italy were recruited with N = 1974 participants in total. In an online survey, participants reported on nutrition and physical activity app use as well as a range of relevant socio-demographic characteristics associated with social inequality according to PROGRESS-Plus (age, gender, education, income, employment status, rural vs. urban residency, Austrian/German/Italian citizenship, migration history, minority status, and sexual orientation).

Except for residency and migration status, all socio-demographic characteristics were associated with mHealth app (non-)use if analysed independently. A latent class analysis revealed four distinct classes of mHealth app (non-)users. ‘Young and diverse citizens’ (characterised by young age and lowest proportion of heterosexuals) and ‘economically strong employees’ (characterised by highest levels of education and income) were more likely to use mHealth apps compared to ‘established retirees’ (characterised by largest share of retired individuals) and ‘low-income workers’ (characterised by lowest levels of education and income).

Age, education, income and employment are crucial inequality indicators for mHealth app use. These results confirm the existence of a digital health divide in Europe that urgently needs addressing to promote digital health for all.

https://osf.io/s2wya (Austria and Germany), https://osf.io/tpu2m (Italy).