Limits...
Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set.

Kaufman TK, Sheehan DM, Rundle A, Neckerman KM, Bader MD, Jack D, Lovasi GS - BMC Res Notes (2015)

Bottom Line: 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.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.Further, standardized approaches to NETS and other "big data" will facilitate the veracity and comparability of results across studies.

View Article: PubMed Central - PubMed

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.

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.

Discussion: 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.

No MeSH data available.


Total number of vigorous physical activity facilities in NY–NJ–PA CBSA 23 counties, for the years 1990–2010, and the effect of treatment of business categorization and potentially duplicative businesses.  Overall category assignment,  yearly category assignment,  overall category assignment, after collapsing potentially duplicative businesses
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4588464&req=5

Fig3: Total number of vigorous physical activity facilities in NY–NJ–PA CBSA 23 counties, for the years 1990–2010, and the effect of treatment of business categorization and potentially duplicative businesses. Overall category assignment, yearly category assignment, overall category assignment, after collapsing potentially duplicative businesses

Mentions: Promising strategies to promote health and prevent chronic conditions include creating new opportunities for physical activity and increasing availability of places to buy healthy foods. Likewise, policies restricting access to resources, such as fast food [37] and alcohol [38], have been considered. While the plots in Fig. 1 assume a simple linear trend over time, more complex temporal trajectories (Figs. 2, 3, 4) or discontinuities may also be of interest, particularly for evaluation of policies shaping the business environment. For example, in New York City (NYC) the Food Retail Expansion to Support Health (FRESH) program provides zoning and financial incentives to promote the establishment of neighborhood grocery stores in underserved communities [39]. Using NETS, one can trace the preceding decades for establishment and retention of new grocery stores and compare to rates of change in supermarket density after program implementation.Fig. 2


Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set.

Kaufman TK, Sheehan DM, Rundle A, Neckerman KM, Bader MD, Jack D, Lovasi GS - BMC Res Notes (2015)

Total number of vigorous physical activity facilities in NY–NJ–PA CBSA 23 counties, for the years 1990–2010, and the effect of treatment of business categorization and potentially duplicative businesses.  Overall category assignment,  yearly category assignment,  overall category assignment, after collapsing potentially duplicative businesses
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4588464&req=5

Fig3: Total number of vigorous physical activity facilities in NY–NJ–PA CBSA 23 counties, for the years 1990–2010, and the effect of treatment of business categorization and potentially duplicative businesses. Overall category assignment, yearly category assignment, overall category assignment, after collapsing potentially duplicative businesses
Mentions: Promising strategies to promote health and prevent chronic conditions include creating new opportunities for physical activity and increasing availability of places to buy healthy foods. Likewise, policies restricting access to resources, such as fast food [37] and alcohol [38], have been considered. While the plots in Fig. 1 assume a simple linear trend over time, more complex temporal trajectories (Figs. 2, 3, 4) or discontinuities may also be of interest, particularly for evaluation of policies shaping the business environment. For example, in New York City (NYC) the Food Retail Expansion to Support Health (FRESH) program provides zoning and financial incentives to promote the establishment of neighborhood grocery stores in underserved communities [39]. Using NETS, one can trace the preceding decades for establishment and retention of new grocery stores and compare to rates of change in supermarket density after program implementation.Fig. 2

Bottom Line: 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.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.Further, standardized approaches to NETS and other "big data" will facilitate the veracity and comparability of results across studies.

View Article: PubMed Central - PubMed

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.

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.

Discussion: 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.

No MeSH data available.