Effective Prevention and Management Tools for Metabolic Syndrome Based on Digital Health-Based Lifestyle Interventions Using Healthcare Devices

Abstract

Digital health-based lifestyle interventions (e.g., mobile applications, short messaging service, wearable devices, social media, and interactive websites) are widely used to manage metabolic syndrome (MetS). This study aimed to confirm the utility of self-care for prevention or management of MetS. We recruited 106 participants with one or more MetS risk factors from December 2019 to September 2020. Participants were provided five healthcare devices and applications. Characteristics were compared at baseline and follow-up to examine changes in risk factors, engagement, persistence, and physical activity (analyzed through device use frequency and lifestyle interventions performed). Participants with 1–2 MetS risk factors showed statistically significant reductions in waist circumference (WC) and blood pressure (BP). Participants with ≥3 MetS risk factors showed statistically significant reductions in risk factors including weight, body mass index, WC, BP, and fasting blood sugar (FBS). The prevention and improvement groups used more healthcare devices than the other groups. Smartwatch was the most frequently used device (5 times/week), and physical activity logged more than 7000 steps/week. WC, BP, and FBS of the improvement group were reduced by more than 40%. Based on engagement, persistence, and physical activity, digital health-based lifestyle interventions could be helpful for MetS prevention and management.

Predicting metabolic syndrome using machine learning – Analysis of commonly used indices

“…33 The use of E-Health apps in most cases is voluntary, but persistence to goals can set the stage for long-term use, thereby promoting more favorable health outcomes. 34 The use of digital health-based lifestyle interventions may increase engagement and persistence in self-healthcare, 35 which is essential in the case of the syndrome.…”

Evaluation of Self-Management Behaviors and Its Correlation with the Metabolic Syndrome among the Type 2 Diabetes Mellitus Patients of Northern Saudi Arabia

“…Numerous pieces of evidence suggest that patients who were identified with MS tend to have a higher risk of developing depression and a lack of support for social activities that help them to implement self-management behaviors such as exercise and diet [ 45 , 46 ]. Simultaneously, poor diabetic self-management behaviors may lead to the development or worsening of MS [ 46 , 47 ].…”

Smart Consumer Wearables as Digital Diagnostic Tools: A Review

“…It was able to detect COVID-19 in the pre-symptomatic period as well as the symptomatic phase of the patients, with a precision score of 0.91 (CI: 0.854–0.967) [ 10 ]. Cho et al proposed a one-class SVM method that can detect COVID-19 23.5–40% earlier compared to the method of Mishra et al [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ,…”

“…Hence, wearables provide a non-invasive, miniaturized, easy-to-operate, and novel method for glucometry, which could be used as an alternative to invasive tools in clinical settings [ 83 ]. In another study reported by Lee et al, smartwatch data along with other digital data were used to enable the better prevention of metabolic syndromes by the continuous detection of several health factors [ 41 ].…”