Identifying the beliefs which predict environmentally friendly behaviour in the Brisbane area : a foundation for informed interventions

A move to more sustainable living can provide immediate and long term health and environmental benefits. The Green Living Study consisted of a mail survey of 1186 South East Queensland residents and an online survey of a further 451 individuals, primarily from South East Queensland, and explored the predictors of environmentally friendly behaviour. This paper explores the underlying beliefs that were found to predict specific environmentally friendly behaviours, such as walking for transport, switching off lights when not in use, switching off unused appliances at the wall and shopping with reusable bags. Beliefs explored included social norms, advantages and disadvantages of performing the behaviours, and issues of control over ones behaviour. The findings showed that people’s environmentally friendly behaviours may be influenced by convenience, saving money and saving face; i.e. is it easy to do, will I be better off, and will I be seen as ‘different’? Understanding the beliefs which directly predict behaviour can help inform public policy and educational initiatives. A number of models for transferring this knowledge into policy and practice will be discussed.

Socio-economic differences in takeaway food consumption among adults

To examine socioeconomic differences in the frequency and types of takeaway foods consumed. Cross-sectional postal survey. Participants were asked about their usual consumption of overall takeaway food (< four times a month, or ≥ four times a month) and 22 specific takeaway food items (< once a month, or ≥ once a month): these latter foods were grouped into “healthy” and “less healthy” choices. Socioeconomic position was measured using education and equivalised household income and differences in takeaway food consumption were assessed by calculating prevalence ratios using log binomial regression. Adults aged 25–64 years from Brisbane, Australia were randomly selected from the electoral roll (N = 903, 63.7% response rate). Compared with their more educated counterparts, the least educated were more regular consumers of overall takeaway food, fruit/vegetable juice, and less regular consumers of sushi. For the “less healthy” items, the least educated more regularly consumed potato chips, savoury pies, fried chicken, and non-diet soft drinks; however, the least educated were less likely to consume curry. Household income was not associated with overall takeaway consumption. The lowest income group were more regular consumers of fruit/vegetable juice compared with the highest income group. Among the “less healthy” items, the lowest income group were more regular consumers of fried fish, ice-cream, and milk shakes, while curry was consumed less regularly. The frequency and types of takeaway foods consumed by socioeconomically disadvantaged groups may contribute to inequalities in overweight/obesity and chronic disease.

The association between objectively measured neighborhood features and walking in middle-aged adults

Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

A multilevel investigation of inequalities in clinical and psychosocial outcomes for women after breast cancer

Background In Australia, breast cancer is the most common cancer affecting Australian women. Inequalities in clinical and psychosocial outcomes have existed for some time, affecting particularly women from rural areas and from areas of disadvantage. We have a limited understanding of how individual and area-level factors are related to each other, and their associations with survival and other clinical and psychosocial outcomes. Methods/Design This study will examine associations between breast cancer recurrence, survival and psychosocial outcomes (e.g. distress, unmet supportive care needs, quality of life). The study will use an innovative multilevel approach using area-level factors simultaneously with detailed individual-level factors to assess the relative importance of remoteness, socioeconomic and demographic factors, diagnostic and treatment pathways and processes, and supportive care utilization to clinical and psychosocial outcomes. The study will use telephone and self-administered questionnaires to collect individual-level data from approximately 3, 300 women ascertained from the Queensland Cancer Registry diagnosed with invasive breast cancer residing in 478 Statistical Local Areas Queensland in 2011 and 2012. Area-level data will be sourced from the Australian Bureau of Statistics census data. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to diagnostic and treatment centres. Data analysis will include a combination of standard empirical procedures and multilevel modelling. Discussion The study will address the critical question of: what are the individual- or area-level factors associated with inequalities in outcomes from breast cancer? The findings will provide health care providers and policy makers with targeted information to improve the management of women with breast cancer, and inform the development of strategies to improve psychosocial care for women with breast cancer.

Food insecurity among Australian children : potential determinants, health and developmental consequences

Children in food-insecure households may be at risk of poor health, developmental or behavioural problems. This study investigated the associations between food insecurity, potential determinants and health and developmental outcomes among children. Data on household food security, socio-demographic characteristics and children’s weight, health and behaviour were collected from households with children aged 3–17 years in socioeconomically disadvantaged suburbs by mail survey using proxy-parental reports (185 households). Data were analysed using logistic regression. Approximately one-in-three households (34%) were food insecure. Low household income was associated with an increased risk of food insecurity [odds ratio (OR), 16.20; 95% confidence interval (CI), 3.52–74.47]. Children with a parent born outside of Australia were less likely to experience food insecurity (OR, 0.42; 95% CI, 0.19–0.93). Children in food-insecure households were more likely to miss days from school or activities (OR, 3.52; 95% CI, 1.46–8.54) and were more likely to have borderline or atypical emotional symptoms (OR, 2.44; 95% CI, 1.11–5.38) or behavioural difficulties (OR, 2.35; 95% CI, 1.04–5.33). Food insecurity may be prevalent among socioeconomically disadvantaged households with children. The potential developmental consequences of food insecurity during childhood may result in serious adverse health and social implications.

Validation of de-identified record linkage to ascertain hospital admissions in a cohort study

Background Cohort studies can provide valuable evidence of cause and effect relationships but are subject to loss of participants over time, limiting the validity of findings. Computerised record linkage offers a passive and ongoing method of obtaining health outcomes from existing routinely collected data sources. However, the quality of record linkage is reliant upon the availability and accuracy of common identifying variables. We sought to develop and validate a method for linking a cohort study to a state-wide hospital admissions dataset with limited availability of unique identifying variables. Methods A sample of 2000 participants from a cohort study (n = 41 514) was linked to a state-wide hospitalisations dataset in Victoria, Australia using the national health insurance (Medicare) number and demographic data as identifying variables. Availability of the health insurance number was limited in both datasets; therefore linkage was undertaken both with and without use of this number and agreement tested between both algorithms. Sensitivity was calculated for a sub-sample of 101 participants with a hospital admission confirmed by medical record review. Results Of the 2000 study participants, 85% were found to have a record in the hospitalisations dataset when the national health insurance number and sex were used as linkage variables and 92% when demographic details only were used. When agreement between the two methods was tested the disagreement fraction was 9%, mainly due to "false positive" links when demographic details only were used. A final algorithm that used multiple combinations of identifying variables resulted in a match proportion of 87%. Sensitivity of this final linkage was 95%. Conclusions High quality record linkage of cohort data with a hospitalisations dataset that has limited identifiers can be achieved using combinations of a national health insurance number and demographic data as identifying variables.