RECVD created a protocol for classifying potentially health-relevant establishments from commercially licensed established data. Our categorization of annual retail location data from the National Establishment Time Series dataset (1990-2014) used 8-digit Standard Industrial Classification codes, informed by prior literature. Systematic spot checks were conducted across 30 locations of varying urbanicity in all 10 US census regions (to inform the inclusion or exclusion of 81 SIC codes in the health-relevant categories establishments). Our protocol was presented at the 2020 Society for Prevention Research, and published in the Journal of Urban Health in 2020.

Hirsch, J.A., Moore, K.A., Cahill, J., Quinn, J., Zhao, Y., Bayer, F.J., Rundle, A. and Lovasi, G.S., 2020. Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology. Journal of Urban Health, pp.1-14.

We have created two categories in the RECVD NETS (1990-2014):

Auxiliary: Auxiliary categories that are defined in relatively small subsets that can be combined into versions that are more tailored to specific outcomes or allow for sensitivity analyses by including or not including certain Auxiliary categories. Not all Auxiliary categories are independent and may overlap. Additionally, some of the categories are not expected to be meaningful when used on their own (e.g. chain pharmacies vs total pharmacies).

Main: Main categories were created as groupings of Auxiliary categories that are most likely to be useful across multiple projects or analyses, limiting the need to make customizations each time and increasing consistency. For most analyses, /purposes the Main categories will be more useful than Auxiliary categories. Individual business records may be found in more than one category due to word and name searches. The primary category for a business is assigned based on its SIC code classification and also according to the results of the word/name search. For example, a “PIZZA HUT” with SIC code of 58120300 would be classified as “Fast Food – SIC code based definition (FFS)” based on SIC code, “Pizza (PIZ)” based on having the word pizza, and “Fast Food Quick Service (QSV)” based on Pizza Hut being included in the Technomics/R&I chain name list.

When combining categories, caution should be taken to ensure individual business records are not double counted. For analysts wishing to construct custom combinations we have created a “hierarchy” version. See the NETS Categories Documentation and the NETS Catalogue (in development) below.

If you have any questions, please contact the RECVD Research Coordinator (gslovasiresearch@gmail.com).

Interactive Diagram of NETS Main & Auxiliary Categories

Click on the interactive diagram below to zoom in on categories of interest.