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Understanding community context and adult health changes in China: development of an urbanicity scale
Jessica C Jones-Smith1, Barry M Popkin
1Department of Nutrition and Carolina Population Center, University of North Carolina at Chapel Hill, University Sq., CB# 8120 123 W. Franklin St., Chapel Hill, NC 27516-3997, USA.
Abstract:
The classification of places as either urban or rural is typically based on an absolute threshold of population and/or population density. However, conceptual definitions of urbanization and urbanicity encompass dimensions beyond solely population size and population density. Multiple important distinguishing urban characteristics beyond population size have been described. The crude classification of places as urban or rural coupled with infrequent updates to this information creates a measure that is prone to misclassification error. An improved measure of urbanicity would draw information from the domains that characterize urban and rural places, would be sensitive to changes over time, and would represent gradations on the continuum from rural to urban environments. The goal of the current study was to develop such a scale from existing data, test whether the scale was reliable and valid, and assess whether it provided information beyond what could be determined from the traditional urban/rural dichotomous variable. We utilized established scaling procedures from the psychometric literature to construct and evaluate a multicomponent scale to measure urban features on a continuum in China. We also provided an example of its potential contribution to health research by examining its relationship with the adult body mass index (BMI). Because the scale was constructed and tested using established scaling procedures and using a wide array of variables, it represents an improvement over previous attempts at such a scale and will provide a reliable and valid measurement tool for researchers in this arena. We demonstrate that the scale predicts the incidence of overweight/obesity populations in China, but it promises to be most useful for other economic, demographic, social welfare, and health outcomes.
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