[Saarland Growth Study: sampling design].
The use of reference data to evaluate the physical development of children and adolescents is part of the daily routine in the paediatric ambulance. The construction of such reference data is based on the collection of extensive reference data. There are different kinds of reference data: cross sectional references, which are based on data collected from a big representative cross-sectional sample of the population, longitudinal references, which are based on follow-up surveys of usually smaller samples of individuals from birth to maturity, and mixed longitudinal references, which are a combination of longitudinal and cross-sectional reference data. The advantages and disadvantages of the different methods of data collection and the resulting reference data are discussed. The Saarland Growth Study was conducted for several reasons: growth processes are subject to secular changes, there are no specific reference data for children and adolescents from this part of the country and the growth charts in use in the paediatric praxis are possibly not appropriate any more. Therefore, the Saarland Growth Study served two purposes a) to create actual regional reference data and b) to create a database for future studies on secular trends in growth processes of children and adolescents from Saarland. The present contribution focusses on general remarks on the sampling design of (cross-sectional) growth surveys and its inferences for the design of the present study.
Psychiatrischen Klinik und Poliklinik, Universitätsklinikums Benjamin Franklin, Freien Universität Berlin. hhopfe@zedat.fu-berlin.de
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D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D002648:Child; D002657:Child Development; D002675:Child, Preschool; D003625:Data Collection / Q000379:methods*; D005260:Female; D005858:Germany; D006128:Growth; D006801:Humans; D008297:Male; D012016:Reference Values; D012107:Research Design / Q000592:standards*; D012494:Sampling Studies; D017678:Sex Distribution; D012959:Socioeconomic Factors