JMIR Publications

ABSTRACT

Background:

Numerous studies have suggested that the relationship between cardiovascular disease (CVD) risk and the utilization of mobile health (mHealth) technology may vary depending on the total number of CVD risk factors present. However, whether higher CVD risk is associated with a greater likelihood of engaging in specific mHealth usage among US adults with or at risk of CVD is currently unknown.

Objective:

To assess the associations between the composite of CVD risk and each component of mHealth usage among US adults with or at risk of CVD.

Methods:

This study used cross-sectional data from the 2017 to 2020 Health Information National Trends Survey. The exposures were CVD risk (diabetes, hypertension, smoking, physical inactivity, and overweight or obesity). We defined low, moderate, and high CVD risk as having 0-1, 2-3, and 4-5 CVD risk factors, respectively. The outcome variables of interest were each component of mHealth usage, including using mHealth to make health decisions, track health progress, share health information, and discuss health decisions with health providers. We used multivariable logistic regression models to examine the association between CVD risk and mHealth usage adjusted for demographic factors.

Results:

We included 10,531 adults, with a mean (± standard deviation) age of 54 (±16.2) years. Among the included participants, 50.2% were male, 65.4% were Non-Hispanic White, 41.9% used mHealth to make health decisions, 50.8% used mHealth to track health progress toward a health-related goal, 18.3% used mHealth to share health information with health providers, and 37.7% used mHealth to discuss health decisions with health providers. Adults with moderate CVD risk were more likely to use mHealth to share health information with health providers (adjusted odds ratio: 1.49, 95% confidence interval [1.24-1.80]), and discuss health decisions with health providers (1.22 [1.04-1.44]) compared to those with low CVD risk. Similarly, having high CVD risk was associated with higher odds of using mHealth to share health information with health providers (2.61 [1.93-3.54]) and discuss health decisions with health providers (1.56 [1.17-2.10]) compared to those with low CVD risk. Upon stratifying by age and gender, we observed age and gender disparities in the relationship between CVD risk and the utilization of mHealth to discuss health decisions with health providers.

Conclusions:

Adults with a greater number of CVD risk factors were more likely to use mHealth to share health information with health providers and discuss health decisions with health providers. These findings suggest a promising avenue for enhancing healthcare communication and advancing both primary and secondary prevention efforts related to managing CVD risk factors through the effective utilization of mHealth technology.