Workout Logging Through an mHealth App for Weight Reduction Among Different Generations: Secondary Analysis of the MED PSU×ThaiSook Healthier Challenge

Author:

Sae-lee KittiyaORCID,Surangsrirat DechoORCID,Parlawong ChanatipORCID,Anawilkul T-touchORCID,Assawachamrun NarinuchORCID,Boonbandan PawanyaORCID,Ladapongpuwat PaweerataORCID,Chupetch BhawatORCID,Thongchai SupatchaORCID,Pruphetkaew NannapatORCID,Thongseiratch TherdpongORCID,Vichitkunakorn PolathepORCID,Ngamchaliew PitchayanontORCID

Abstract

Background Being overweight or obese presents a major risk factor for noncommunicable diseases (NCDs) such as cardiovascular disease, diabetes, and musculoskeletal disorders. These problems are preventable and solvable via weight reduction and increased physical activity and exercise. The number of adults who are overweight or affected by obesity has tripled in the last 4 decades. Using mobile health (mHealth) apps can help users with health issues, including reducing their weight by restricting their daily calorie intake, which can be recorded along with other parameters, such as physical activity and exercise. These features could further enhance health and prevent NCDs. ThaiSook, a Thai mHealth app developed by the National Science and Technology Development Agency, aims to promote healthy lifestyles and reduce the risk behaviors of NCDs. Objective This study aimed to determine whether ThaiSook users were successful in 1-month weight reduction and identify which demographic factors or logging functions were associated with significant weight reduction. Methods A secondary data analysis was performed using data collected from the “MED PSU×ThaiSook Healthier Challenge,” a month-long challenge to encourage a healthy lifestyle. We enrolled 376 participants to evaluate the study outcomes. The variables, comprising demographic characteristics (ie, sex, generation, group size, and BMI), were classified into 4 groups: normal (18.5-22.9 kg/m2), overweight (23-24.9 kg/m2), obese I (25-29.9 kg/m2), and obese II (BMI ≥30 kg/m2). Logging functions (ie, water, fruit and vegetables, sleep, workout, step, and run) were classified into 2 groups: consistent (≥80%) and inconsistent (<80%) users. Weight reduction was categorized into 3 groups: no weight reduction, slight weight reduction (0%-3%), and significant weight reduction (>3%). Results Of 376 participants, most were female (n=346, 92%), had normal BMI (n=178, 47.3%), belonged to Generation Y (n=147, 46.7%), and had a medium group size (6-10 members; n=250, 66.5%). The results showed that 56 (14.9%) participants had 1-month significant weight loss, and the median weight reduction of the group was −3.85% (IQR −3.40% to −4.50%). Most participants (264/376, 70.2%) experienced weight loss, with an overall median weight loss of −1.08% (IQR −2.40% to 0.00%). The factors associated with significant weight reduction were consistently logging workouts (adjusted odds ratio [AOR] 1.69, 95% CI 1.07-2.68), being Generation Z (AOR 3.06, 95% CI 1.01-9.33), and being overweight or being obese compared to those with normal BMI (AOR 2.66, 95% CI 1.41-5.07; AOR 1.76, 95% CI 1.08-2.87, respectively). Conclusions More than half of the “MED PSU×ThaiSook Healthier Challenge” participants achieved a slight weight reduction, and 14.9% (56/376) of users lost significant weight. Factors including workout logging, being Generation Z, being overweight, and being obese were associated with significant weight reduction.

Publisher

JMIR Publications Inc.

Subject

Health Informatics,Medicine (miscellaneous)

Reference42 articles.

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