Improving diet, activity and wellness in adults at risk of diabetes: randomized controlled trial.
Sommaire de l'article
The purpose of this analysis is to examine the effect of an algorithm-driven online diabetes prevention program on changes in eating habits, physical activity and wellness/productivity factors.
The intervention, Alive-PD, used small-step individually tailored goal setting and other features to promote changes in diet and physical activity. A 6-month randomized controlled trial was conducted among patients from a healthcare delivery system who had confirmed prediabetes (n =339). Change in weight and glycemic markers were measured in the clinic. Changes in physical activity, diet and wellness/productivity factors were self-reported. Mean age was 55 (s.d. 8.9) years, mean body mass index was 31 (s.d. 4.4) kg m(-2), 68% were white and 69% were male.
The intervention group increased fruit/vegetable consumption by 3.71 (95% confidence interval (CI) 2.73, 4.70) times per week (effect size 0.62), and decreased refined carbohydrates by 3.77 (95% CI 3.10, 4.44) times per week both significantly (P<0.001) greater changes than in the control group. The intervention group also reported a significantly greater increase in physical activity than in the control group, effect size 0.49, P<0.001. In addition, the intervention group reported a significant increase in self-rated health, in confidence in ability to make dietary changes and in ability to accomplish tasks, and a decrease in fatigue, compared with the control group. These changes paralleled the significant treatment effects on glycemic markers and weight.
In addition to promoting improvements in weight and glycemic markers, the Alive-PD program appears to improve eating habits and physical activity, behaviors important not just for diabetes prevention but for those with diagnosed diabetes or obesity. The improvements in wellness/productivity may derive from the diet and activity improvements, and from the satisfaction and self-efficacy of achieving goals.