An ecological analysis of factors associated with food insecurity in South Australia, 2002-7.
OBJECTIVE
To estimate the extent of food insecurity in South Australia and its relationship with a variety of socio-economic variables.


METHODS
Data collected routinely from 2002 to 2007 by SA Health were analysed to explore food security in the State's population. An ecological analysis of data collected by the South Australian Monitoring and Surveillance System (SAMSS) that collects data on key health indicators. Questions on food security are asked periodically from July 2002 to December 2007.


METHODS
South Australia.


METHODS
Over 37,000 interviewees took part in SAMSS surveys. Questions about food security were asked of 19,037 subjects. The sample was weighted by area, age and gender so that the results were representative of the South Australian population.


RESULTS
Seven per cent (1342/19,037) of subjects reported running out of food during the previous year and not having enough money to buy food (food insecurity). Logistic regression analysis found food insecurity to be highest in households with low levels of education, limited capacity to save money, Aboriginal households, and households with three or more children.


CONCLUSIONS
The study confirms that food insecurity is strongly linked to economic disadvantage. Increasing cost of food is likely to exacerbate food insecurity. This is of concern given that food insecurity is associated with poor health, especially obesity and chronic disease. Comprehensive action at all levels is required to address root causes of food insecurity. Regular surveillance is required to continue to monitor levels of food security, but more in-depth understandings, via qualitative research, would be useful.
Foley
Wendy
W
Department of Public Health, Flinders University, GPO Box 2100, Adelaide, South Australia 5001, Australia.
Ward
Paul
P
Carter
Patricia
P
Coveney
John
J
Tsourtos
George
G
Taylor
Anne
A
D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D004522:Educational Status; D004651:Employment; D005260:Female; D005523:Food Supply / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D006815:Hunger; D007223:Infant; D007231:Infant, Newborn; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009749:Nutrition Surveys; D011159:Population Surveillance; D011203:Poverty / Q000208:ethnology; D015995:Prevalence; D012307:Risk Factors; D012959:Socioeconomic Factors; D013021:South Australia / Q000453:epidemiology; D055815:Young Adult