Spatial and Semantic Validation of Secondary Food Source Data

ISPRS International Journal of Geo-Information

Anders K. Lyseen¹ 

关键词: spatial;    semantic;    public health nutrition;    food environments;    geographical information systems;    measurement;   

DOI  :  10.3390/ijgi3010236

来源: mdpi

【 摘 要 】

Governmental and commercial lists of food retailers are often used to measure food environments and foodscapes for health and nutritional research. Information about the validity of such secondary food source data is relevant to understanding the potential and limitations of its application. This study assesses the validity of two government lists of food retailer locations and types by comparing them to direct field observations, including an assessment of whether pre-classification of the directories can reduce the need for field observation. Lists of food retailers were obtained from the Central Business Register (CVR) and the Smiley directory. For each directory, the positive prediction value (PPV) and sensitivity were calculated as measures of completeness and thematic accuracy, respectively. Standard deviation was calculated as a measure of geographic accuracy. The effect of the pre-classification was measured through the calculation of PPV, sensitivity and negative prediction value (NPV). The application of either CVR or Smiley as a measure of the food environment would result in a misrepresentation. The pre-classification based on the food retailer names was found to be a valid method for identifying approximately 80% of the food retailers and limiting the need for field observation.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.