Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada

Datos Bibliográficos

ID15095260
AutoresMadeleine I G Daepp (0000-0001-9689-2442, Massachusetts Institute of Technology, autor de correspondencia), J L Black (0000-0003-2048-5968, University of British Columbia), Jennifer Black (0000-0002-7534-9886)
Año2017
Volumen20
Número15
Páginas2649-2659
Fecha de publicación2017-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaPublic Health Nutrition (JOURNAL)
Identificadores de la revistaISSN: 1368-9800 • E-ISSN: 1475-2727
EditorialCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s1368980017001744
PMID28816109
OpenAlexW2747873990
IdiomaEN
Citas recibidas10
Referencias citadas44

Objective The present study assessed systematic bias and the effects of data set error on the validity of food environment measures in two municipal and two commercial secondary data sets. Design Sensitivity, positive predictive value (PPV) and concordance were calculated by comparing two municipal and two commercial secondary data sets with ground-truthed data collected within 800 m buffers surrounding twenty-six schools. Logistic regression examined associations of sensitivity and PPV with commercial density and neighbourhood socio-economic deprivation. Kendall’s τ estimated correlations between density and proximity of food outlets near schools constructed with secondary data sets v . ground-truthed data. Setting Vancouver, Canada. Subjects Food retailers located within 800 m of twenty-six schools Results All data sets scored relatively poorly across validity measures, although, overall, municipal data sets had higher levels of validity than did commercial data sets. Food outlets were more likely to be missing from municipal health inspections lists and commercial data sets in neighbourhoods with higher commercial density. Still, both proximity and density measures constructed from all secondary data sets were highly correlated (Kendall’s τ >0·70) with measures constructed from ground-truthed data. Conclusions Despite relatively low levels of validity in all secondary data sets examined, food environment measures constructed from secondary data sets remained highly correlated with ground-truthed data. Findings suggest that secondary data sets can be used to measure the food environment, although estimates should be treated with caution in areas with high commercial density

Concordance · Data collection · Data set · Environmental health · Geography · Logistic regression · Missing data · Neighbourhood (mathematics · Statistics · Mathematics · Medicine · Nutritional Studies and Diet · Obesity, Physical Activity, Diet · Urban Transport and Accessibility