TY - JOUR
T1 - Government data v. ground observation for food-environment assessment
T2 - Businesses missed and misreported by city and state inspection records
AU - Lucan, Sean C.
AU - Maroko, Andrew R.
AU - Abrams, Courtney
AU - Rodriguez, Noemi
AU - Patel, Achint N.
AU - Gjonbalaj, Ilirjan
AU - Schechter, Clyde B.
AU - Elbel, Brian
N1 - Funding Information:
Acknowledgements: The authors would like to thank Tod Mijanovich, Jessica Athens and Erilia Wu for help with data preparation and cleaning, and for assistance with data analysis. The authors would also like to acknowledge the following individuals for their help in translating the data-collection sheet used in interacting with street vendors: Nandini Deb and Mahbooba Akhter Kabita for assistance with translation into Bengali; Gustavo Hernandez and Monica Varona for assistance with translation into Spanish. S.C.L. would like to acknowledge A. Hal Strelnick for mentorship. Funding support: S.C.L. is supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health (award number K23HD079606). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Student stipends from the Albert Einstein College of Medicine helped support data collection. For data collection and management, the study used REDCap electronic data capture tools hosted through the Harold and Muriel Block Institute for Clinical and Translational Research at Einstein and Montefiore (under grant number UL1 TR001073). This work was also partially supported by the New York Regional Center for Diabetes Translation Research (under grant P30 DK111022). The NYU School of Medicine helped support data cleaning and analyses (through grant number R01DK097347). The funders had no additional role in the design, analysis or writing of this article. Conflict of interest: None of the authors have any conflicts to report. Authorship: S.C.L. co-conceived the study, conducted the literature review, designed the data-collection protocol, oversaw primary data collection, performed analyses and drafted the manuscript (including tables and figure). A.R.M. guided the sampling strategy, performed geocoding and linking of data sets, assisted with data analyses and data interpretation, and created maps for the figure. A.N.P. and I.G. performed primary data collection and assisted with data analysis and interpretation. C.A. helped coordinate acquisition of the government data sets and oversaw match determinations between government data and ground observation. N.R. helped clean the data and make match determinations between data sets. C.B.S. oversaw and conducted data analysis and assisted with data interpretation. B.E. co-conceived the study and provided critical input at all stages. All authors helped revise the manuscript. Ethics of human subject participation: This study did not involve human subjects. Primary data collection from 2015 was approved by the Albert Einstein College of Medicine Institutional Review Board, as part of a broader study, under federal regulations 45 CFR 46.110 and 21 CFR 56.110.
Publisher Copyright:
© The Authors 2019.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - Objective: To assess the accuracy of government inspection records, relative to ground observation, for identifying businesses offering foods/drinks.Design: Agreement between city and state inspection records v. ground observations at two levels: businesses and street segments. Agreement could be 'strict' (by business name, e.g. 'Rizzo's') or 'lenient' (by business type, e.g. 'pizzeria'); using sensitivity and positive predictive value (PPV) for businesses and using sensitivity, PPV, specificity and negative predictive value (NPV) for street segments.Setting: The Bronx and the Upper East Side (UES), New York City, USA.Participants: All food/drink-offering businesses on sampled street segments (n 154 in the Bronx, n 51 in the UES).Results: By 'strict' criteria, sensitivity and PPV of government records for food/drink-offering businesses were 0·37 and 0·57 in the Bronx; 0·58 and 0·60 in the UES. 'Lenient' values were 0·40 and 0·62 in the Bronx; 0·60 and 0·62 in the UES. Sensitivity, PPV, specificity and NPV of government records for street segments having food/drink-offering businesses were 0·66, 0·73, 0·84 and 0·79 in the Bronx; 0·79, 0·92, 0·67, and 0·40 in the UES. In both areas, agreement varied by business category: restaurants; 'food stores'; and government-recognized other storefront businesses ('gov. OSB', i.e. dollar stores, gas stations, pharmacies). Additional business categories - 'other OSB' (barbers, laundromats, newsstands, etc.) and street vendors - were absent from government records; together, they represented 28·4 % of all food/drink-offering businesses in the Bronx, 22·2 % in the UES ('other OSB' and street vendors were sources of both healthful and less-healthful foods/drinks in both areas).Conclusions: Government records frequently miss or misrepresent businesses offering foods/drinks, suggesting caveats for food-environment assessments using such records.
AB - Objective: To assess the accuracy of government inspection records, relative to ground observation, for identifying businesses offering foods/drinks.Design: Agreement between city and state inspection records v. ground observations at two levels: businesses and street segments. Agreement could be 'strict' (by business name, e.g. 'Rizzo's') or 'lenient' (by business type, e.g. 'pizzeria'); using sensitivity and positive predictive value (PPV) for businesses and using sensitivity, PPV, specificity and negative predictive value (NPV) for street segments.Setting: The Bronx and the Upper East Side (UES), New York City, USA.Participants: All food/drink-offering businesses on sampled street segments (n 154 in the Bronx, n 51 in the UES).Results: By 'strict' criteria, sensitivity and PPV of government records for food/drink-offering businesses were 0·37 and 0·57 in the Bronx; 0·58 and 0·60 in the UES. 'Lenient' values were 0·40 and 0·62 in the Bronx; 0·60 and 0·62 in the UES. Sensitivity, PPV, specificity and NPV of government records for street segments having food/drink-offering businesses were 0·66, 0·73, 0·84 and 0·79 in the Bronx; 0·79, 0·92, 0·67, and 0·40 in the UES. In both areas, agreement varied by business category: restaurants; 'food stores'; and government-recognized other storefront businesses ('gov. OSB', i.e. dollar stores, gas stations, pharmacies). Additional business categories - 'other OSB' (barbers, laundromats, newsstands, etc.) and street vendors - were absent from government records; together, they represented 28·4 % of all food/drink-offering businesses in the Bronx, 22·2 % in the UES ('other OSB' and street vendors were sources of both healthful and less-healthful foods/drinks in both areas).Conclusions: Government records frequently miss or misrepresent businesses offering foods/drinks, suggesting caveats for food-environment assessments using such records.
KW - Food environment
KW - Food stores
KW - Mobile food vendors
KW - Restaurants
KW - Secondary data
KW - Street vendors
KW - Urban
KW - Validation
UR - http://www.scopus.com/inward/record.url?scp=85082673765&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082673765&partnerID=8YFLogxK
U2 - 10.1017/S1368980019002982
DO - 10.1017/S1368980019002982
M3 - Article
C2 - 31680658
AN - SCOPUS:85082673765
SN - 1368-9800
VL - 23
SP - 1414
EP - 1427
JO - Public Health Nutrition
JF - Public Health Nutrition
IS - 8
ER -