Abstract
Issue addressed: Food insecurity, now listed among the social determinants of health, compromises the health and well-being of affected Australians. The objective of this study was to determine the prevalence of food insecurity within an urban population of social disadvantage in readiness for a local health promotion response.
Abstract
Methods: This was a cross-sectional survey conducted in three disadvantaged locations of south-western Sydney. Prevalence of food insecurity was assessed using both the 16-item US Household Food Security Survey Module and the single-item question previously used in national Australian health surveys. Bivariate and multiple logistic regression analyses were performed to determine associations between food insecurity and socio-demographic characteristics of the households.
Abstract
The 16-item US tool yielded a significantly higher food insecurity prevalence (21.9%, 95% CI 20.0-23.8) than the single-item Australian tool (15.8%, 95% CI 14.1-17.5). Compared with the former, the single-item Australian tool has high specificity (96%) yet low sensitivity (56.9%). In our three sites, food insecurity was strongly and independently associated with household capacity to save money (AOR=5.05). Local fruit and vegetable production (83.8%), nutrition education (83.9%), transport to food outlets (81.5%) and better public transport overall (76.3%) were most highly rated by 'food insecure' households as useful future strategies.
Abstract
The higher sensitivity of the US 16-item food security survey module relative to the single-item Australian tool indicates its potential for use in future Australian surveys of food insecurity.
Introduction
Despite Australia's relative affluence and abundant food supply, sections of its population are likely to be food insecure.
Introduction
1 Food insecurity is defined as "the limited or uncertain availability of nutritionally adequate and safe foods or limited or uncertain ability to acquire acceptable foods in socially acceptable ways". 2 Food insecurity is associated with poor health and insidiously exacerbates other health inequalities.
Introduction
1, 3 It is recognised as an important social determinant of health 4, 5 and has been identified as a significant Australian public health issue at national 6 and state 7 levels.
Introduction
Food, nutrition and household economics are likely linked 3 and have been explored in previous Australian 8, 9 and New Zealand 10 surveys. Research has shown that groups at high risk of food insecurity include those on low incomes, 1, 3 and that food purchasing behaviours of socio-economically disadvantaged
So what?
In the absence of strategies already proven to make a difference to food insecurity, the findings of this study will inform the initiation of local health promotion interventions addressing inequities identified by food-insecure households of Sydney South West Area Health Service and add to the evidence base.
So what?
groups are least in accord with dietary guideline recommendations. 5, 11, 12 In addition to income, studies suggest that food access and food supply also contribute to food insecurity.
So what?
1, 13 Food access generally refers to capacity to acquire and consume a healthy diet, including ability to buy and transport food; home storage, preparation and cooking facilities; knowledge and skills to make appropriate choices; and time and mobility to shop for and prepare food.
So what?
1 Food supply refers to aspects of the supply of food within a community affecting food security of individuals, households or an entire population, specifically location of food outlets, availability of food within stores, price, quality and variety of available food. 1 Previous efforts to estimate population prevalence of food insecurity in Australia include the 1995 Australian National Nutrition Survey 14 and the New South Wales Child Health Survey 2001. 15 Both used a single-item measure that is more an indicator of risk rather than a measure of food insecurity. 3 By contrast, a more comprehensive measure of food insecurity prevalence has been used in the United States (US) that particularly assesses the degree of hunger experienced by foodinsecure households. 16 This more comprehensive tool, which assesses the nature and severity of food insecurity, will provide unique Australian data that will inform a health promotion response. At the local level, any actions to alleviate food insecurity require descriptive and analytic data beyond that generated by the single-item tool. 1, 3 Given criticisms of the validity of the single-item Australian tool as a measure of food insecurity prevalence, 3 this study aimed to report the prevalence of food insecurity in Sydney South West Area Health Service (SSWAHS) using both the single-item Australian tool and the more comprehensive measure that has been used in the US, and to determine local residents' understanding of food insecurity and priorities for intervention among those most in need. It was considered that this survey would provide quantitative baseline data in anticipation of a future rigorous evaluation of the impact of subsequent health promotion action to alleviate food insecurity.
Method Study setting
Of the 177 local government areas (LGAs) in New South Wales (NSW), seven are located in south-western Sydney and aggregate socio-economic status for each of the LGAs can be measured by the Socio-Economic Index for Areas (SEIFA). 17 Using SEIFA for 2001 Census data, 84% of the population of south-western Sydney resides in LGAs ranked in the lowest 40% of SEIFA rankings. 18 Of even greater concern, 63% of the south-western Sydney population resides in LGAs ranked in the bottom quintile (20%) in NSW. 18 Hence, three lowest-ranked postcodes from the three most disadvantaged LGAs (one from each) were purposely selected as sampling frames for the present study to access the degree of severity of food insecurity in south-western Sydney. Table 1 summarises socio-economic information about the three sites from which the postcodes were selected, referred to herein as WF, VL and RA. For comparison, similar information for NSW is also included in Table 1 . 
Survey administration
A random sample of households from each of WF, VL and RA was generated from an electronic version of the White Pages telephone directory. To maximise response rates, address listings in this database were used to mail an advance informative letter about our study seven days prior to the intended telephone contact to all randomly selected households. At least 10 call attempts were then made by one of 25 trained interviewers from a market research company to establish contact with each household. One eligible person was identified per household, namely the person aged 18 years of age or older who was responsible for doing "most of the cooking and food shopping". Verbal consent to participate in our interview was then obtained. All interviewers were Interviewer Quality Control Australia (IQCA) trained and certified.
Survey administration
After verbal consent was obtained, the interviewer proceeded to administer the 25-minute, computer-assisted telephone interview (CATI). Interviews were mostly conducted in the evenings or at other times arranged for the respondent's convenience. Multi-lingual interviewing was offered in the five languages most commonly spoken in these three sites, namely English, Arabic, Cantonese or Mandarin, Spanish and Vietnamese. 17 The interview was originally developed in English, then back-translated by a commercial translation service then checked by bilingual SSWAHS health workers for accuracy of meaning. When an interviewer encountered a respondent with language difficulties, they ascertained which language the respondent spoke and, if it was one of the languages offered, a call-back was arranged. In these instances, multi-lingual interviewers had translated hard-copy versions of the household survey from which they read questions. Responses were entered directly into English CATI. Validations of responses were conducted via live monitoring of 10% of interviews using standard IQCA forms. Interviews were conducted between June and August 2004.
Survey instrument
The instrument used for the household survey (available from the authors on request) included background demographics and two measures of food insecurity. The first measure of food insecurity, developed by the US Department of Agriculture and known as the US Household Food Security Survey Module, 16 is referred to herein as the '16-item US tool'. The 16-item US tool, described in detail by the authors elsewhere, 16 addressed the following: a screening question about whether the household had enough of the kinds of food they/we want to eat (n=1), concerns about food running out and having enough money to get more (n=2), ability to afford balanced meals (n=1), having enough money to adequately feed children (n=3); adults skipping meals (n=2) or eating less (n=1) because of inadequate money to buy food, weight loss due to insufficient money to purchase food (n=1), and adults not eating for a whole day (n=1). Lastly, four questions addressed capacity to feed children (under 18 years of age), specifically: cutting size of meals, skipping meals, being hungry, and not eating for a whole day. The second measure of food insecurity used in the interview, the Australian single-item measure (herein referred to as the 'single-item Australian tool') 1,8,9 posed one question as follows: In the past 12 months, were there any times that you ran out of food and couldn't afford to buy more? ('yes', 'no', 'unsure' 'refused'). Households responding 'yes' to this question were next asked whether they had used each of nine coping strategies, adapted from published research.
15
Further questions in the survey instrument addressed aspects of transport related to food insecurity dimensions (developed de novo) and the respondent's involvement in the community. [19] [20] [21] In order to inform local population health interventions, respondents' endorsement was sought of 13 listed strategies for future implementation in their community. These strategies have the potential to address food supply and access factors, and were adapted from existing policy frameworks.
1,22-25

Statistical procedures
SPSS (Version 12.1) 26 and Epi Info (Version 6) 27 were used for all analyses. Because of variation of the number of households per site, the total prevalence estimate for all three sites (combined total) was calculated based on weights constructed from the number of households in each site (identified by listed telephone number). The number of households experiencing food insecurity was calculated based on the US 16-item score and Australian single-item response respectively. Based on the US 16-item score, in accordance with the author's recommended guidelines, 16 households were categorised into one of four categories: food secure (scores of 0-2.2), food insecure without hunger (scores of >2.2, ≤4.4), food insecure with moderate hunger (>4.4, ≤6.4) and food insecure with severe hunger (scores of >6.4, <10). Household categories determined from the 16-item US tool were then dichotomised into two groups for analyses: 'food secure' and 'food insecure' (total of 'food insecure without hunger', 'food insecure with moderate hunger' and 'food insecure with severe hunger'). Based upon the Australian tool, households indicating 'yes' to the single item question were classified as food insecure, those indicating 'no' were classified as food secure.
Statistical procedures
Sensitivity and specificity of the single-item Australian tool were compared with the 16-item US tool, using a standard 2x2 table.
Statistical procedures
To quantify community involvement, responses to each of five questions were first dichotomised then summed to generate a score from zero (lowest possible community connection) to five (highest possible community connection). For some analyses, the score was further classified as follows: 'low' (score=0 or 1), 'medium' (score=2 or 3) and 'high' (score=4 or 5).
Statistical procedures
Bivariate (cross-tabulations) and forced entry multiple logistic regression analyses 28 were performed to determine associations between food insecurity and socio-economic and demographic characteristics of the households (explanatory variables). Results of bivariate analyses were expressed as percentages and chisquare tests were used to examine group differences (p<0.05). Logistic regression analysis determined the independent contribution of each potential explanatory variable on household food insecurity adjusting for other variables. Adjusted odds ratios (AOR) from logistic regression analysis with their 95% confidence intervals (95% CI) express the likelihood of food insecurity for each explanatory variable adjusted for the effects of other variables. Only those variables found significant in bivariate analyses were included in the logistic regression model. To avoid multi-collinearity among the highly correlated variables, the variable that had less influence over others (in terms of food insecurity) were excluded from the logistic regression model.
Sample size calculations
It was hypothesised that the prevalence of food insecurity might be as high as 10% within each of the three designated sites. In anticipation of further evaluation of the impact of local strategies designed to decrease food insecurity, a sample size in each site sufficient to detect a 3% change in prevalence (80% power, 95% CI) was sought. Samples of 651 households per site were sufficient to enable a prevalence estimate of food insecurity as low as 7% with a precision of 2% (±2%) with 95% CI. 
Ethical approval

Results

Response rate and sample characteristics
In total, 4,239 south-western Sydney household telephone numbers were generated from the Electronic White Pages: WF (n=913), VL (n=1,828) and RA (n=1,498) respectively. Of these, 1,922 were deemed ineligible after 10 attempts for the following reasons: disconnected (n=771), engaged (n=1), no answer (n=683), business number (n=91), fax/modem (n=29), moved out of area (n=60), too frail to interview (n=113) or spoke a language other than those available (n=174). From 2,317 eligible phone listings, 1,719 interviews were completed in total (overall response rate 74%). Due to an unexpectedly high number of disconnected numbers in WF (nearly 200, out of 913), the required sample size was not obtained at that site despite calling all numbers. Response rates for WF (n=413, 84%), VL (n=651, 72%) and RA (n=655, 71%) were not significantly different (p=0.10). Most interviews were conducted in English (n=1,535, 89.3%) with fewer in Arabic (n=79, 4.6%), Cantonese/ Mandarin (n=44, 2.6%), Spanish (n=32, 1.9%) or Vietnamese (n=29, 1.7%). 
Prevalence of food insecurity

Coping strategies used by food-insecure households (single-item Australian tool)
Households indicating 'yes' to the single-item Australian tool, when next asked about nine strategies that families often use to cope when they run out of food and can't afford to buy more, indicated that only three cited strategies were used by the majority, specifically: cutting down on the variety of household food (59.1%, 95% CI 53.4-64.8), putting off paying bills (57.4%, 95% CI 51.6-63.1) and the parent or guardian skipping meals or eating less (58.8%, 95% CI 53.0-64.4).
Independent predictors of food insecurity (16-item US tool)
Bivariate analysis first confirmed there was no significant association between gender and education of respondent with food insecurity as measured by the 16-item US tool.
Independent predictors of food insecurity (16-item US tool)
There was no significant association between 'community involvement score' ('low', 'medium', 'high') and food insecurity (16-item US score) (p=0.89). All other household and individual demographic variables were significantly associated with food insecurity (bivariate analyses available from the authors). Food insecurity also was significantly associated with difficulty accessing shops (transport) and each of six aspects of food supply and each of seven aspects of food access (bivariate analyses available from the authors). Factors significantly (p<0.05) associated with food insecurity as determined by the 16-item US tool in these bivariate analyses then were included in the logistic regression model to determine the independent contribution of each after adjusting for all other factors. Table 4 displays results from the logistic regression model. All except two of the variables entered in the model remained statistically significant (see Table 4 ). Four predictors were found to have relatively strong associations (AOR≥2), namely capacity to save, presence of children in the household, housing tenure and respondents' reported health status (see Table 4 ). Indeed, households that could not save were five times more likely to be food insecure than households than could save (AOR=5.05, 95% CI 3.0-7.10). Those who were renting were nearly three times more likely to be food insecure compared with those who owned or had mortgages (AOR=2.77, 95% CI 1.81-4.24). Households with children less than 18 years of age were more than twice as likely to be food insecure as households with no children (AOR=2.13, 95% CI 1.53-2.96).
Accessing shops to buy food
When asked about their usual mode of transport to access shops to buy food, most south-western Sydney households used a car (79.8%, 95% CI 78-81.7). Nearly one in five respondents indicated it was 'difficult' accessing shops using their usual mode of transport (18.3%); of these, more than one-third (37.9%) were households classified as 'food insecure' (16-item US tool). Further, of the food-insecure households indicating difficulty accessing shops, more than one-quarter cited that this was due to reduced mobility caused by disability, illness or injury (25.7%, 95% CI 17.9-33.3). Difficulties shopping with children (15.0%, 95% CI 8.9-21.5) and absolute distance to shops (12.8%, 95% CI 6.9-18.7) also were highly ranked. Table 5 lists food insecure households' ratings of 13 listed for furture community action. The proportion of food-insecure households typically exceeded that of food secure households in their ratings of local food production, improved transport to food outlets and health education on food and nutrition.
Preferred strategies to facilitate change

Conclusions
To our knowledge, this is the first Australian survey of food insecurity among low socio-economic households addressing the recognised need to provide evidence applicable specifically to this target group. 1, 29 Our results, which show higher specificity of the 16-item US tool over the single-item Australian tool, suggest that the prevalence of food insecurity within the Australian community, both advantaged and disadvantaged, may have been masked in previous surveys.
Conclusions
Although quantitative, our study has provided additional insights about potential predictors of food insecurity identified by those most in need, previously under-published in Australia. Specifically, this is also the first Australian study to quantify 'supply' and 'access' as predictors of household food insecurity. 'Ability to access shops', 'price of food' and having 'adequate time to shop, prepare and cook food' independently predicted household food insecurity. As most respondents indicated using a car to access shops, it was not surprising that absolute 'distance to food shops' and 'reliable and adequate public transport' were not independently predictive of food insecurity. The high rating of transport strategies by all households suggests that it is a simplistic hypothesis that anyone with a car won't ever need public transport.
Conclusions
The findings that 'price of food' also predicted food insecurity contextualises previous (albeit dated) reports that healthier foods cost more in south-western Sydney. 30 As cost is an important determinant in choice of food, 30 low-income families of southwestern Sydney may be forced to choose cheaper rather than healthier foods. A New Zealand report on food insecurity demonstrated the high cost of a healthy diet relative to welfare payments or minimum wages, and that while overall low-income families are good at budgeting they have insufficient money for all their basic needs. 13 Food-insecure families are caught in a vicious cycle and have difficulty in obtaining food at the lowest prices because of lack of transport, storage or money to buy food in bulk, 13 while it is often the shops most accessible that are most expensive. 31 This relationship between income and food security status is further supported by our findings that households with no capacity to save money were five times more likely to be food insecure than households that could save.
Conclusions
Clearly, in south-western Sydney and at a state and national level, a broad whole-of-government approach to address the social and economic determinants of food insecurity (such as income, housing, cost of food), including a rise in real incomes whether from minimum wage or social assistance, protecting the affordability of food staples (such as milk), ensuring affordable housing and establishing a national food insecurity monitoring system to determine progress, deterioration or shifts among those affected, is indicated. 4 Twelve of 13 strategies to improve access to food were supported by all households surveyed, demonstrating that the required community support indicated as necessary for local food security initiatives 3 is present in south-western Sydney. The most highly rated strategies included: local food production; midstream interventions likely to have a long-term impact on food insecurity 1 ; improved transport to food outlets; upstream interventions that reduce structural barriers to food insecurity; 1 and nutrition education. While nutrition education can be an important and effective strategy for improving diet, the effectiveness of such initiatives on food insecurity is dependent upon the availability of appropriate resources and skills 1 and on healthy food being readily available and accessible. 5 It is suggested that a community-level focus on midstream and, where possible, longer-term upstream initiatives is likely to have the greatest impact on food insecurity. 1 Our data will assist our health service to identify relevant alliances for comprehensive, intersectoral and social intervention in response to the communities' needs. 3 Efforts to address structural issues underpinning food insecurity, such as poverty and geographical isolation, appear warranted to reduce the high prevalence of food insecurity. We theorise that this approach coupled with local initiatives (including community development) that emphasise food skills and alternative means of food acquisition would likely be well received if offered as part of our intervention and could be a useful adjunct to social and economic forces underlying food insecurity. 32 We acknowledge the limitations of generalising these results nationally, but believe the methodology will be of considerable interest to those working in the area of food insecurity. Our telephone survey excluded households without a landline connection and the homeless. The study was limited to the five major languages spoken within south-western Sydney, potentially excluding minority or newly emerging groups who are likely to be at an increased risk of food insecurity. 3 Nonetheless, we argue that the inadequacy of the single-item Australian tool is demonstrated, reaffirming recommendations to use the 16-item US tool nationally not only in stand-alone descriptive research but also in any study that, like ours, is intended to provide insight about interventions and a baseline for evaluation over time. We also acknowledge the limitations in the inclusiveness of our food supply and food access choices, these being based upon previous surveys and policy frameworks.
1,15
Hence, we believe that our survey tool, which incorporates a comprehensive measure of food insecurity, is well suited to inform local health promotion initiatives that potentially will meet the needs of the population most at risk of food insecurity.
1,15
1, 3 The evidence generated from this survey instrument can also be used at a broader level for local and national-level advocacy, to influence policy making, and to increase population understanding of the complex nature of food insecurity in order to engage the necessary workforce and government to address food insecurity at all levels of society.

{'paper_id': '20439207', 'title': 'Food insecurity in three socially disadvantaged localities in Sydney, Australia', 's2_url': 'https://api.semanticscholar.org/CorpusID:20439207', 'source': 'S2ORC'}