Fast-food exposure around schools in urban Adelaide

Neil COFFEE, Hannah Kennedy, Theo NIYONSENGA

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Objective To assess whether exposure to fast-food outlets around schools differed depending on socio-economic status (SES). Design Binary logistic regression was used to investigate the presence and zero-inflated Poisson regression was used for the count (due to the excess of zeroes) of fast food within 1000 m and 15000 m road network buffers around schools. The low and middle SES tertiles were combined due to a lack of significant variation as the 'disadvantaged' group and compared with the high SES tertile as the 'advantaged' group. School SES was expressed using the 2011 Australian Bureau of Statistics, socio-economic indices for areas, index of relative socio-economic disadvantage. Fast-food data included independent takeaway food outlets and major fast-food chains. Setting Metropolitan Adelaide, South Australia. Subjects A total of 459 schools were geocoded to the street address and 1000 m and 1500 m road network distance buffers calculated. Results There was a 1·6 times greater risk of exposure to fast food within 1000 m (OR=1·634; 95 % 1·017, 2·625) and a 9·5 times greater risk of exposure to a fast food within 1500 m (OR=9·524; 95 % CI 3·497, 25·641) around disadvantaged schools compared with advantaged schools. Conclusions Disadvantaged schools were exposed to more fast food, with more than twice the number of disadvantaged schools exposed to fast food. The higher exposure to fast food near more disadvantaged schools may reflect lower commercial land cost in low-SES areas, potentially creating more financially desirable investments for fast-food developers.

Original languageEnglish
Pages (from-to)3095-3105
Number of pages11
JournalPublic Health Nutrition
Volume19
Issue number17
DOIs
Publication statusPublished - 2016
Externally publishedYes

Fingerprint

Fast Foods
Vulnerable Populations
Economics
Buffers
Geographic Mapping
South Australia
Food Chain
Logistic Models

Cite this

@article{d3c5c921ed3847c38b022958d16904a1,
title = "Fast-food exposure around schools in urban Adelaide",
abstract = "Objective To assess whether exposure to fast-food outlets around schools differed depending on socio-economic status (SES). Design Binary logistic regression was used to investigate the presence and zero-inflated Poisson regression was used for the count (due to the excess of zeroes) of fast food within 1000 m and 15000 m road network buffers around schools. The low and middle SES tertiles were combined due to a lack of significant variation as the 'disadvantaged' group and compared with the high SES tertile as the 'advantaged' group. School SES was expressed using the 2011 Australian Bureau of Statistics, socio-economic indices for areas, index of relative socio-economic disadvantage. Fast-food data included independent takeaway food outlets and major fast-food chains. Setting Metropolitan Adelaide, South Australia. Subjects A total of 459 schools were geocoded to the street address and 1000 m and 1500 m road network distance buffers calculated. Results There was a 1·6 times greater risk of exposure to fast food within 1000 m (OR=1·634; 95 {\%} 1·017, 2·625) and a 9·5 times greater risk of exposure to a fast food within 1500 m (OR=9·524; 95 {\%} CI 3·497, 25·641) around disadvantaged schools compared with advantaged schools. Conclusions Disadvantaged schools were exposed to more fast food, with more than twice the number of disadvantaged schools exposed to fast food. The higher exposure to fast food near more disadvantaged schools may reflect lower commercial land cost in low-SES areas, potentially creating more financially desirable investments for fast-food developers.",
keywords = "Fast-food exposure, Geographic information system, Schools, Socio-economic status, Residence Characteristics, Fast Foods, Social Class, South Australia",
author = "Neil COFFEE and Hannah Kennedy and Theo NIYONSENGA",
year = "2016",
doi = "10.1017/S1368980016001385",
language = "English",
volume = "19",
pages = "3095--3105",
journal = "Public Health Nutrition",
issn = "1368-9800",
publisher = "Cambridge University Press",
number = "17",

}

Fast-food exposure around schools in urban Adelaide. / COFFEE, Neil; Kennedy, Hannah; NIYONSENGA, Theo.

In: Public Health Nutrition, Vol. 19, No. 17, 2016, p. 3095-3105.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Fast-food exposure around schools in urban Adelaide

AU - COFFEE, Neil

AU - Kennedy, Hannah

AU - NIYONSENGA, Theo

PY - 2016

Y1 - 2016

N2 - Objective To assess whether exposure to fast-food outlets around schools differed depending on socio-economic status (SES). Design Binary logistic regression was used to investigate the presence and zero-inflated Poisson regression was used for the count (due to the excess of zeroes) of fast food within 1000 m and 15000 m road network buffers around schools. The low and middle SES tertiles were combined due to a lack of significant variation as the 'disadvantaged' group and compared with the high SES tertile as the 'advantaged' group. School SES was expressed using the 2011 Australian Bureau of Statistics, socio-economic indices for areas, index of relative socio-economic disadvantage. Fast-food data included independent takeaway food outlets and major fast-food chains. Setting Metropolitan Adelaide, South Australia. Subjects A total of 459 schools were geocoded to the street address and 1000 m and 1500 m road network distance buffers calculated. Results There was a 1·6 times greater risk of exposure to fast food within 1000 m (OR=1·634; 95 % 1·017, 2·625) and a 9·5 times greater risk of exposure to a fast food within 1500 m (OR=9·524; 95 % CI 3·497, 25·641) around disadvantaged schools compared with advantaged schools. Conclusions Disadvantaged schools were exposed to more fast food, with more than twice the number of disadvantaged schools exposed to fast food. The higher exposure to fast food near more disadvantaged schools may reflect lower commercial land cost in low-SES areas, potentially creating more financially desirable investments for fast-food developers.

AB - Objective To assess whether exposure to fast-food outlets around schools differed depending on socio-economic status (SES). Design Binary logistic regression was used to investigate the presence and zero-inflated Poisson regression was used for the count (due to the excess of zeroes) of fast food within 1000 m and 15000 m road network buffers around schools. The low and middle SES tertiles were combined due to a lack of significant variation as the 'disadvantaged' group and compared with the high SES tertile as the 'advantaged' group. School SES was expressed using the 2011 Australian Bureau of Statistics, socio-economic indices for areas, index of relative socio-economic disadvantage. Fast-food data included independent takeaway food outlets and major fast-food chains. Setting Metropolitan Adelaide, South Australia. Subjects A total of 459 schools were geocoded to the street address and 1000 m and 1500 m road network distance buffers calculated. Results There was a 1·6 times greater risk of exposure to fast food within 1000 m (OR=1·634; 95 % 1·017, 2·625) and a 9·5 times greater risk of exposure to a fast food within 1500 m (OR=9·524; 95 % CI 3·497, 25·641) around disadvantaged schools compared with advantaged schools. Conclusions Disadvantaged schools were exposed to more fast food, with more than twice the number of disadvantaged schools exposed to fast food. The higher exposure to fast food near more disadvantaged schools may reflect lower commercial land cost in low-SES areas, potentially creating more financially desirable investments for fast-food developers.

KW - Fast-food exposure

KW - Geographic information system

KW - Schools

KW - Socio-economic status

KW - Residence Characteristics

KW - Fast Foods

KW - Social Class

KW - South Australia

UR - http://www.scopus.com/inward/record.url?scp=84976536881&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/fastfood-exposure-around-schools-urban-adelaide

U2 - 10.1017/S1368980016001385

DO - 10.1017/S1368980016001385

M3 - Article

VL - 19

SP - 3095

EP - 3105

JO - Public Health Nutrition

JF - Public Health Nutrition

SN - 1368-9800

IS - 17

ER -