The worldwide prevalence of obesity is considered as a serious issue because obesity is one of the main causes of diabetes, heart disease, and cancer. Obesity is associated with various habits of our daily life, e.g. short sleep duration, high alcohol intake, and nonparticipation in physical exercise. Therefore, changing these habits in order to reduce body weight is recognized as an effective solution. There are some websites in effort to monitor obesity, which verify the usefulness of web-based system for health-care support. We, the authors, propose an obesity prevention system that helps users to change their lifestyles with a website and health care devises. The system detects whether each user has the habits that generally considered as risk factors of obesity. After the detection, the system analyzes personal factors of weight gain, and informs it to the user for changing the habits effectively. Since calorie intake is an important factor of weight gain, we have developed 3 different types of dietary information logging methods. In addition, we evaluated and compared these methods by experiments, and we found that simple methods with a piece of data is enough to estimate calorie intake, instead of detailed methods with a lot of data. Moreover, we conducted another experiment for evaluating the factor analysis by predicting fluctuation of fat mass. In the experiment, the detected factors were useful for predicting the fluctuation of fat mass, therefore, we think these factors can be used for preventing obesity.