JMIR Publications

ABSTRACT

Background:

Health is a key indicator of social and economic development, while health inequality—advocated by WHO as critical for individual, family, and societal health. Digitalization, as an emerging factor influencing health and health inequality, has come under attention in research. However, research on specific digital engagement behaviors has relatively limited dimensions, primarily focusing on engagement frequency. Regarding health inequality, scholars tend to emphasize the impact of internet access or coverage on health disparities, yet pay less attention to health differences arising from variations in internet usage.

Objective:

This study aimed to explore the heterogeneous association of digital engagement on health and health inequality, and focus on three perspectives: (1) health disparities in association across individuals with varying health levels; (2) association of specific digital engagement behaviors with health and health inequality; and (3) the moderating role of socioeconomic status.This study aimed to explore the heterogeneous association of digital engagement on health and health inequality, and focus on three perspectives: (1) health disparities in association across individuals with varying health levels; (2) association of specific digital engagement behaviors with health and health inequality; and (3) the moderating role of socioeconomic status.

Methods:

From July-Sept 2024, 7725 valid participants were selected via multi-stage stratified sampling in the eastern, central and western regions of China. Short-video software use was selected as a core indicator of internet use, given its dominance in digital engagement and health information acquisition. Health was measured by self-rated health, while health inequality was measured by relative health deprivation (RD). Quantile regression was used to explore the association of short-video use with health and health inequality. Linear regression explored the relationship between multi-dimensional use and health, as well as health inequality, including years, frequency, duration of use. Interaction analysis tested socioeconomic status’s moderation.

Results:

Of 7725 participants, 57% used short-video software. Quantile regression showed there were better self-rated health at 20th - 90th quantiles (strongest at 50th: β=2.729, P<0.001) and lower RD at 10th - 80th quantiles (strongest at 50th: β=-0.020, P<0.001) among the users of short-video software. But no association was founded at 10th (self-rated health) and 90th (RD) quantiles. Linear regression revealed longer use years and shorter daily duration had significant correlations with better self-rated health and lower RD. Socioeconomic status moderated thDigital engagement has a heterogeneous association on health and health inequality, benefiting middle-health groups most but not vulnerable ones. Socioeconomic status moderates the effect, supporting targeted digital health policies to reduce inequality.e duration-RD association and DUS had the strongest promoting effect on reducing RD in the high socioeconomic status group.

Conclusions:

Digital engagement has a heterogeneous association on health and health inequality, benefiting middle-health groups most but not vulnerable ones. Socioeconomic status moderates the effect, supporting targeted digital health policies to reduce inequality.