Introduction
Metabolic syndrome (MetS) is characterized by abdominal obesity, elevated blood pressure, dyslipidemia, and impaired glucose regulation, and it substantially increases the risk of type 2 diabetes and cardiovascular disease. Lifestyle modification, including healthy diet and regular physical activity, is the cornerstone of MetS prevention and management. Web-based interventions have emerged as a convenient and accessible way to deliver lifestyle advice and behavioral support, particularly given widespread internet access. However, a major challenge in online trials is attrition, including low adherence (non-usage) and dropout (loss to follow-up). Previous research has reported high dropout rates in web-based interventions, ranging from 40% to 60%, and suggested that interventions often reach people with more resources and better health. Few studies have examined adherence and attrition specifically in web-based lifestyle programs for MetS. Therefore, this study aimed to evaluate adherence and attrition rates and identify predictors of dropout in a web-based lifestyle intervention among adults with MetS.
Methods
Study Design and Participants
This 6-month, two-arm RCT was conducted in Tehran, Iran, between June and August 2012. Participants were recruited via a public health website focused on heart health. Eligible participants were aged ≥20 years, resided in Tehran, and met the ATP III criteria for MetS: waist circumference ≥90 cm, blood pressure ≥130/85 mmHg, plus at least one other MetS component. Exclusion criteria included cardiovascular disease, diabetes, use of antihypertensive or lipid-lowering medications, and pregnancy. A total of 160 participants completed baseline assessments and were randomly assigned to either the intervention group (n=80) or the control group (n=80). Randomization was performed using a 1:1 allocation ratio with block size of four.
Intervention
- Intervention group: Received login access to an interactive website, “My Healthy Heart Profile,” which provided educational content updated every two weeks, personalized tracking of MetS risk factors, visual feedback on progress, and opportunities to ask questions online.
- Control group: Received general health information by email every three weeks, including advice on healthy nutrition, fruit and vegetable intake, physical activity, and weight management, but had no access to the interactive platform.
Assessments
Data were collected at baseline, 3 months, and 6 months. Measures included demographics, anthropometrics (weight, height, waist circumference), blood pressure, fasting blood glucose, lipid profiles, physical activity (IPAQ short form), and health-related quality of life (SF-36). The SF-36 consists of eight subscales: physical functioning, role physical, bodily pain, general health, vitality, social functioning, role emotional, and mental health. Higher scores indicate better quality of life. Adherencewas defined as completing both 3- and 6-month follow-up assessments. Attrition was defined as failure to complete either follow-up.
Statistical Analysis
Descriptive statistics (mean, standard deviation, frequency, percentage) were used to summarize baseline characteristics. Chi-square and t-tests were applied to compare groups. Generalized Estimating Equations (GEE) were used to examine predictors of attrition across follow-up time points. A P-value < 0.05 was considered statistically significant.
Results
Participant Characteristics
The mean age of participants was 44.5 ± 10 years; 66.3% were male, 83.8% married, and 71.3% employed. Average internet use was 12.2 hours per week. Baseline anthropometric and cardiometabolic parameters were similar between groups, except for LDL-cholesterol, which was slightly higher in the intervention group.
Adherence and Attrition Rates
- At 3 months, attrition was 20% in both intervention and control groups.
- At 6 months, overall attrition was 26.9%. The control group had significantly higher attrition (33.7%) than the intervention group (20%, P < 0.001).
Predictors of Attrition (GEE)
- Education: Participants with ≤12 years of education were nearly three times more likely to drop out (OR=2.95, 95%CI: 1.39–6.33, P=0.05).
- Weight: Higher body weight was associated with increased attrition (OR=1.04, 95%CI: 1.00–1.10, P=0.05).
- Quality of life: Lower scores in general health, social functioning, vitality, and mental health significantly predicted dropout (all P < 0.05).
- Study duration: At 6 months, attrition was lower than at 3 months (OR=0.66, 95%CI: 0.52–0.83, P < 0.001).
Quality of Life Differences
Participants who remained in the study had significantly higher vitality and mental health scores at baseline compared with those who dropped out (P < 0.001).
Discussion
This study found that a web-based lifestyle intervention significantly reduced long-term attrition among adults with MetS. The interactive platform likely enhanced engagement through personalized feedback, regular updates, and ongoing access to health information. However, the results also confirmed that participants who stayed in the program were more educated and had better baseline quality of life, while those who dropped out were less educated, heavier, and reported poorer mental health and vitality. These findings support the concern that web-based interventions often fail to reach the most vulnerable populations—those with lower education, fewer resources, and poorer health.
Several factors may explain higher dropout among less educated participants, including lower health literacy, limited familiarity with online tools, and difficulty maintaining motivation without in-person support. Poorer mental health and vitality may reduce participants’ ability to engage in self-directed online interventions. The reduction in attrition at 6 months compared with 3 months suggests that participants who persist beyond the first few months may develop stable habits and greater commitment.
Limitations include the lack of data on non-usage attrition (e.g., login frequency) and the limited generalizability to populations outside Tehran or with different internet access patterns. Future studies should incorporate objective usage metrics and explore barriers to engagement among low-education and low–quality-of-life subgroups.
Conclusion
Web-based lifestyle interventions can improve retention among adults with MetS, but they disproportionately retain participants with higher education and better quality of life. To maximize public health impact, interventions must be redesigned with tailored, low-literacy-friendly content, simplified navigation, and multi-channel support to engage the most vulnerable individuals with MetS.
