title: Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set.
abstract: BACKGROUND
  The densities of food retailers, alcohol outlets, physical activity facilities, and medical facilities have been associated with diet, physical activity, and management of medical conditions. Most of the research, however, has relied on cross-sectional studies. In this paper, we assess methodological issues raised by a data source that is increasingly used to characterize change in the local business environment: the National Establishment Time Series (NETS) dataset.
  
  
  CONCLUSIONS
  Longitudinal data, such as NETS, offer opportunities to assess how differential access to resources impacts population health, to consider correlations among multiple environmental influences across the life course, and to gain a better understanding of their interactions and cumulative health effects. Longitudinal data also introduce new data management, geoprocessing, and business categorization challenges. Examining geocoding accuracy and categorization over 21 years of data in 23 counties surrounding New York City (NY, USA), we find that health-related business environments change considerably over time. We note that re-geocoding data may improve spatial precision, particularly in early years. Our intent with this paper is to make future public health applications of NETS data more efficient, since the size and complexity of the data can be difficult to exploit fully within its 2-year data-licensing period. Further, standardized approaches to NETS and other "big data" will facilitate the veracity and comparability of results across studies.
authors.affiliation: Department of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, 8th Floor, New York, NY, 10032, USA. tkk2109@columbia.edu.|NYC Department of Health and Mental Hygiene, Brooklyn District Public Health Office, 485 Throop Avenue, Brooklyn, New York, NY, 11221, USA. tkk2109@columbia.edu.
authors.forename: Tanya K
authors.initials: TK
authors.lastname: Kaufman
authors.affiliation: Department of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, 8th Floor, New York, NY, 10032, USA. dms2203@columbia.edu.
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Sheehan
authors.affiliation: Department of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, 8th Floor, New York, NY, 10032, USA. agr3@columbia.edu.
authors.forename: Andrew
authors.initials: A
authors.lastname: Rundle
authors.affiliation: Columbia Population Research Center, 1255 Amsterdam Avenue, Room 715, New York, NY, 10027, USA. kmn2@columbia.edu.
authors.forename: Kathryn M
authors.initials: KM
authors.lastname: Neckerman
authors.affiliation: Department of Sociology, Center on Health, Risk and Society, American University, Battelle-Thompkins T-15, 4400 Massachusetts Ave., N.W., Washington DC, 20016, USA. bader@american.edu.
authors.forename: Michael D M
authors.initials: MD
authors.lastname: Bader
authors.affiliation: Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, 722 West 168th Street, 11th Floor, New York, NY, 10032, USA. dj2183@columbia.edu.
authors.forename: Darby
authors.initials: D
authors.lastname: Jack
authors.affiliation: Department of Epidemiology, Columbia University Mailman School of Public Health, 722 West 168th Street, 8th Floor, New York, NY, 10032, USA. glovasi@columbia.edu.
authors.forename: Gina S
authors.initials: GS
authors.lastname: Lovasi
mesh_terms: D003132:Commerce; D019992:Databases as Topic; D003695:Delivery of Health Care; D006282:Health Personnel; D006801:Humans; D008137:Longitudinal Studies; D009043:Motor Activity; D013997:Time Factors