Prevention of the Metabolic Syndrome by New Lifestyle Intervention Methods

Overview

This intervention aims to reduce obesity by using new type of nutritional and lifestyle therapy and in parallel, tailored persuasive information and communications technology (ICT)-technology based application. The study hypothesis is that obesity cannot be reduced just by distributing nutritional information. Instead, by influencing also the eating behavior, permanent lifestyle changes can be achieved. The effect of the therapy along the time-line, the health information literacy of the study persons and the changes in it will be studied at different phases of the intervention. The research will be carried out in three main groups of different levels of nutritional therapies with a parallel ICT-intervention and control group for each main group (altogether six groups).

The research objectives of this study: 1) to find the best counseling methods for improving eating behavior (group counseling, tailored web-based counseling), 2) to find the predictors of successful lifestyle changes and weight loss, 3) to find the associations with biological and psychological eating behavior regulation system, 4) to study the long-term effects of the intervention, 5) to investigate the changes to the medications after the intervention . The study hypothesis is that new theoretically valid cognitive-behavioral-therapy -based counseling methods in combination with ICT support based on persuasive design improve eating behavior, weight loss and self-efficacy and reduce risk factors for the metabolic syndrome, type 2 diabetes, coronary heart disease and musculoskeletal factors. The study population consists of participants with overweight or obesity and at least one risk factor of metabolic syndrome (MetSyn). A population-based sample of 600 participants living in the Oulu area (approx. 200 000 habitants) is collected with the help of the Finnish Population Register Centre. Inclusion criteria include also the ability to use basic ICT technology (email etc.). Exclusion criteria are certain uncontrolled health factors, such as abnormal laboratory values (thyroid, kidney and liver function tests) or clinically significant illness with contraindication for weight loss or physical activity. Study visits are at baseline, 1, 2 and 5 years. At the study visit blood samples are drawn at the research laboratory of the Oulu University Hospital. Along with the timeline of the visits the eating behaviour factors (emotional eating, uncontrolled eating and cognitive restraint), health information literacy (HIL), nutrition habits, smoking, alcohol consumption, medication and previous diseases are recorded by a detailed questionnaires sent to study persons by e-mail. The blood pressure, waist diameter, height and weight are also measured during the visit. All the operations have been described in detail and accepted by the regional Ethics Committee of the Northern Ostrobothnia. The randomization process is two-phased. First the subjects who are included in the study are randomized into 2 different kinds of lifestyle face-to-face counselling groups and one control group. After that they are randomized into users or non-users of the web-based ICT-program "Onnikka". As a summary, there are six different counselling groups: 1) Intensive group counselling, 2) Intensive group counselling with Onnikka, 3) Short term group counselling, 4) Short term counselling with Onnikka, 5) Control group (no intervention at all), and 6) Only Onnikka. A linear mixed-effect model (LMM) (as primary analysis), where group (six study arms) and time were fixed effect factors are used to examine the differences in weight from baseline to 1, 2 and 5 years adjusting for age and sex. Primary analysis and sensitivity analyses are based on intention-to-treat principles. Primary analysis are also used to examine the differences between ICT groups and non-ICT groups. Group and time interaction are included in the model to examine whether mean change over time is different between groups. If data include missing values, they will be assumed to be completely at random. The same model is used with imputed values (both last observation carried forward (LOCF) and return-to-baseline (RTB) where data are missing and for completers as sensitivity analyses. Area Under the Curve (AUC) analysis is performed to integrate the effect interventions on the weight reduction over the different time points.