The Demographic Representativeness and Health Outcomes of Digital Health Station Users: Longitudinal Study

Author:

Flitcroft LeahORCID,Chen Won SunORCID,Meyer DennyORCID

Abstract

Background Digital health stations offer an affordable and accessible platform for people to monitor their health; however, there is limited information regarding the demographic profile of users and the health benefits of this technology. Objective This study aimed to assess the demographic representativeness of health station users, identify the factors associated with repeat utilization of stations, and determine if the health status of repeat users changed between baseline and final health check. Methods Data from 180,442 health station users in Australia, including 8441 repeat users, were compared with 2014-2015 Australian National Health Survey (NHS) participants on key demographic and health characteristics. Binary logistic regression analyses were used to compare demographic and health characteristics of repeat and one-time users. Baseline and final health checks of repeat users were compared using McNemar tests and Wilcoxon signed rank tests. The relationship between the number of checks and final health scores was investigated using generalized linear models. Results The demographic profile of SiSU health station users differs from that of the general population. A larger proportion of SiSU users were female (100,814/180,442, 55.87% vs 7807/15,393, 50.72%), younger (86,387/180,442, 47.88% vs 5309/15,393, 34.49% aged less than 35 years), and socioeconomically advantaged (64,388/180,442, 35.68% vs 3117/15,393, 20.25%). Compared with NHS participants, a smaller proportion of SiSU health station users were overweight or obese, were smokers, had high blood pressure (BP), or had diabetes. When data were weighted for demographic differences, only rates of high BP were found to be lower for SiSU users compared with the NHS participants (odds ratio [OR] 1.26; P<.001). Repeat users were more likely to be female (OR 1.37; P<.001), younger (OR 0.99; P<.001), and from high socioeconomic status areas—those residing in socioeconomic index for areas quintiles 4 and 5 were significantly more likely to be repeat users compared with those residing in quintile 1 (OR 1.243; P<.001 and OR 1.151; P<.001, respectively). Repeat users were more likely to have a higher BMI (OR 1.02; P<.001), high BP (OR 1.15; P<.001), and less likely to be smokers (OR 0.77; P<.001). Significant improvements in health status were observed for repeat users. Mean BMI decreased by 0.97 kg/m2 from baseline to final check (z=−14.24; P<.001), whereas the proportion of people with high BP decreased from 15.77% (1080/6848) to 12.90% (885/6860; χ21=38.2; P<.001). The proportion of smokers decreased from 11.91% (1005/8438) to 10.13% (853/8421; χ21=48.4; P<.001). Number of repeat health checks was significantly associated with smoking status (OR 0.96; P<.048) but not with higher BP (P=.14) or BMI (P=.23). Conclusions These findings provide valuable insight into the benefits of health stations for self-monitoring and partially support previous research regarding the effect of demographics and health status on self-management of health.

Publisher

JMIR Publications Inc.

Subject

Health Informatics

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