Published in:
Open Access 01-12-2008 | Study protocol
The SMILE study: a study of medical information and lifestyles in Eindhoven, the rationale and contents of a large prospective dynamic cohort study
Published in: BMC Public Health | Issue 1/2008
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Background
Health problems, health behavior, and the consequences of bad health are often intertwined. There is a growing need among physicians, researchers and policy makers to obtain a comprehensive insight into the mutual influences of different health related, institutional and environmental concepts and their collective developmental processes over time.
Methods/Design
SMILE is a large prospective cohort study, focusing on a broad range of aspects of disease, health and lifestyles of people living in Eindhoven, the Netherlands. This study is unique in its kind, because two data collection strategies are combined: first data on morbidity, mortality, medication prescriptions, and use of care facilities are continuously registered using electronic medical records in nine primary health care centers. Data are extracted regularly on an anonymous basis. Secondly, information about lifestyles and the determinants of (ill) health, sociodemographic, psychological and sociological characteristics and consequences of chronic disease are gathered on a regular basis by means of extensive patient questionnaires. The target population consisted of over 30,000 patients aged 12 years and older enrolled in the participating primary health care centers.
Discussion
Despite our relatively low response rates, we trust that, because of the longitudinal character of the study and the high absolute number of participants, our database contains a valuable set of information.
SMILE is a longitudinal cohort with a long follow-up period (15 years). The long follow-up and the unique combination of the two data collection strategies will enable us to disentangle causal relationships. Furthermore, patient-reported characteristics can be related to self-reported health, as well as to more validated physician registered morbidity. Finally, this population can be used as a sampling frame for intervention studies. Sampling can either be based on the presence of certain diseases, or on specific lifestyles or other patient characteristics.