Socio-economic inequalities in women`s fruit and vegetable intakes: a multilevel study of individual, social and environmental mediators

Objective: This study employed a multilevel design to test the contribution of individual, social and environmental factors to mediating socio-economic status (SES) inequalities in fruit and vegetable consumption among women. Design: A cross-sectional survey was linked with objective environmental data. Setting: A community sample involving 45 neighbourhoods. Subjects: In total, 1347 women from 45 neighbourhoods provided survey data on their SES (highest education level), nutrition knowledge, health considerations related to food purchasing, and social support for healthy eating. These data were linked with objective environmental data on the density of supermarkets and fruit and vegetable outlets in local neighbourhoods. Results: Multilevel modelling showed that individual and social factors partly mediated, but did not completely explain, SES variations in fruit and vegetable consumption. Store density did not mediate the relationship of SES with fruit or vegetable consumption. Conclusions: Nutrition promotion interventions should focus on enhancing nutrition knowledge and health considerations underlying food purchasing in order to promote healthy eating, particularly among those who are socio-economically disadvantaged. Further investigation is required to identify additional potential mediators of SES–diet relationships, particularly at the environmental level.

Personal, social and environmental determinants of educational inequalities in walking: a multilevel study

Objective: To investigate the contribution of personal, social and environmental factors to mediating socioeconomic (educational) inequalities in women’s leisure-time walking and walking for transport.
Methods: A community sample of 1282 women provided survey data on walking for leisure and transport; educational level; enjoyment of, and self-efficacy for, walking; physical activity barriers and intentions; social support for physical activity; sporting/recreational club membership; dog ownership; and perceived environmental aesthetics and safety. These data were linked with objective environmental data on the density of public open space and walking tracks in the women’s local neighbourhood, coastal proximity and street connectivity.
Results: Multilevel modelling showed that different personal, social and environmental factors were associated with walking for leisure and walking for transport. Variables from all three domains explained (mediated) educational inequalities in leisure-time walking, including neighbourhood walking tracks; coastal proximity; friends’ social support; dog ownership; self-efficacy, enjoyment and intentions. On the other hand, few of the variables examined explained educational variations in walking for transport, exceptions being neighbourhood, coastal proximity, street connectivity and social support from family.
Conclusions: Public health initiatives aimed at promoting, and reducing educational inequalities in, leisure-time walking should incorporate a focus on environmental strategies, such as advocating for neighbourhood walking tracks, as well as personal and social factors. Further investigation is required to better understand the pathways by which education might influence walking for transport.

Overcoming data constraints to create meaningful ecological models

Many techniques used to model ecosystems cannot be meaningfully applied to large-scale ecological problems due to data constraints. Disparate collection methods, data types and incomplete data sets, or limited theoretical understanding mean that a wide range of modelling techniques used to model physical processes or for problems specific to species or populations cannot be used at an ecosystem scale. In developing an ecological response model for the Coorong, a South Australian hypersaline estuary, we combined several flexible modelling approaches in a statistical framework to develop an approach we call ‘ecosystem states’. This model uses simulated hydrodynamic conditions as input to predict one of a suite of states per space and time, allowing prediction of likely ecological conditions under a variety of scenarios. Each ecosystem state has defined sets of biota and physico-chemical parameters. The existing model is limited in that its predictions have yet to be tested and, as yet, no spatial or temporal connectivity has been incorporated into simulated time series of ecosystem states. This approach can be used in a wide range of ecosystems, where enough data are available to model ecosystem states. We are in the process of applying the technique to a nearby lake system. This has been more difficult than for the Coorong as there is little overlap in the spatial and temporal coverage of biological data sets for that region. The approach is robust to low-quality biological data and missing environmental data, so should suit situations where community or management monitoring programs have occurred through time.

Data quality issues in the GIS modelling of air pollution and cardiovascular mortality in Bangalore

Cardiovascular disease (CVD) is the world's number one cause of mortality. Research in recent years has begun to illustrate a significant association between CVD and air pollution. As most of these studies employed traditional statistics, cross-sectional or meta-analysis methods, a study undertaken by the authors was designed to investigate how a geographical information system (GIS) could be used to develop a more efficient spatio-temporal method of analysis than the currently existing methods mainly based on statistical inference. Using Bangalore, India, as a case study, demographic, environmental and CVD mortality data was sought from the city. However, critical deficiencies in the quality of the environmental data and mortality records were identified and quantified. This paper discusses the shortcomings in the quality of mortality data, together with the development of a framework based on WHO guidelines to improve the defects, henceforth considerably improving data quality.

Evaluation of heat stress indices using physiological comparisons in an alumina refinery in a sub-tropical climate

The production of alumina involves the use of a process known as the Bayer process. This method involves the digestion of raw bauxite in sodium hydroxide at temperatures around 250°C. The resultant pregnant liquor then goes through a number of filtering and precipitation processes to obtain the aluminium oxide crystals which are then calcined to obtain the final product. The plant is situated in a sub tropical climate in Northern Australia and this combined with the hot nature of the process results in a potential for heat related illnesses to develop. When assessing a work environment for heat stress a heat stress index is often employed as a guideline and to date the Wet Bulb Globe Temperature (WBGT) has been the recommended index. There have been concerns over the past that the WBGT is not suited to the Northern Australian climate and in fact studies in other countries have suggested this is the case. This study was undertaken in the alumina plant situated in Gladstone Queensland to assess if WBGT was in fact the most suitable index for use or if another was more applicable. To this end three indices, Wet Bulb Globe Temperature (WBGT), Heat Stress Index (HSI) and Required Sweat Rate (SWreq) were compared and assessed using physiological monitoring of heart rate and surrogate core temperature. A number of different jobs and locations around the plant were investigated utilising personal and environmental monitoring equipment. These results were then collated and analysed using a computer program written as part of the study for the manipulation of the environmental data . Physiological assessment was carried out using methods approved by international bodies such as National Institute for Occupational Safety & Health (NIOSH) and International Standards Organisation (ISO) and incorporated the use of a ‘Physiological Factor’ developed to enable the comparison of predicted allowable exposure times and strain on the individual. Results indicated that of the three indices tested, Required Sweat Rate was found to be the most suitable for the climate and in the environment of interest. The WBGT system was suitable in areas in the moderate temperature range (ie 28 to 32°C) but had some deficiencies above this temperature or where the relative humidity exceeded approximately 80%. It was however suitable as a first estimate or first line indicator. HSI over-estimated the physiological strain in situations of high temperatures, low air flows and exaggerated the benefit of artificial air flows on the worker in certain environments ie. fans.

Scaling up community-based obesity prevention in Australia : background and evaluation design of the health promoting communities : being active eating well initiative

Background : There is only limited evidence available on how best to prevent childhood obesity and community-based interventions hold promise, as several successful interventions have now been published. The Victorian Government has recently funded six disadvantaged communities across Victoria, Australia for three years to promote healthy eating and physical activity for children, families, and adults in a community-based participatory manner. Five of these intervention communities are situated in Primary Care Partnerships and are the subject of this paper. The interventions will comprise a mixture of capacity-building, environmental, and whole-of-community approaches with targeted and population-level interventions. The specific intervention activities will be determined locally within each community through stakeholder and community consultation. Implementation of the interventions will occur through funded positions in primary care and local government. This paper describes the design of the evaluation of the five primary care partnership-based initiatives in the 'Go for your life' Health Promoting Communities: Being Active Eating Well (HPC:BAEW) initiative.

Methods/Design : A mixed method and multi-level evaluation of the HPC:BAEW initiative will capture process, impact and outcome data and involve both local and state-wide evaluators. There will be a combined analysis across the five community intervention projects with outcomes compared to a comparison group using a cross-sectional, quasi-experimental design. The evaluation will capture process, weight status, socio-demographic, obesity-related behavioral and environmental data in intervention and comparison areas. This will be achieved using document analysis, paper-based questionnaires, interviews and direct measures of weight, height and waist circumference from participants (children, adolescents and adults).

Discussion : This study will add significant evidence on how to prevent obesity at a population level in disadvantaged and ethnically diverse communities. The outcomes will have direct influence on policy and practice and guide the development and implementation of future obesity prevention efforts in Australia and internationally.

Predicting future ecological degradation based on modelled thresholds

Threshold models are becoming important in determining the ecological consequences of our actions within the environment and have a key role in setting bounds on targets used by natural resource managers. We have been using thresholds and related concepts adapted from the multiple stable-states literature to model ecosystem response in the Coorong, the estuary for Australia’s largest river. Our modelling approach is based upon developing a state-and-transition model, with the states defined by the biota and the transitions defined by a classification and regression tree (CART) analysis of the environmental data for the region. Here we explore the behaviour of thresholds within that model. Managers tend to plan for a set of often arbitrarily-derived thresholds in their natural resource management. We attempt to assess how the precision afforded by analyses such as CART translates into ecological outcomes, and explicitly trial several approaches to understanding thresholds and transitions in our model and how they might be relevant for management. We conclude that the most promising approach would be a mixture of further modelling (using past behaviour to predict future degradation) in conjunction with targeted experiments to confirm the results. Our case study of the Coorong is further developed, particularly for the modelling stages of the protocol, to provide recommendations to improve natural resource management strategies that are currently in use.

Do food and physical activity environments vary between disadvantaged urban and rural areas? Findings from the READI study

Issues addressed: The presence or absence of amenities in local neighbourhood environments can either promote or restrict access to opportunities to engage in healthy and/or less healthy behaviours. Rurality is thought to constrain access to facilities and services. This study investigated whether the presence and density of environmental amenities related to physical activity and eating behaviours differs between socioeconomically disadvantaged urban and rural areas in Victoria, Australia.

Methods: We undertook cross-sectional analysis of environmental data collected in 2007-08 as part of the Resilience for Eating and Activity Despise Inequality (READI) study. These data were sourced and analysed for 40 urban and 40 rural socioeconomically disadvantaged areas. The variables examined were the presence, raw count, count/km², and count/'000 population of a range of environmental amenities (fast-food restaurants, all supermarkets (also separated by major chain and other supermarkets), greengrocers, playgrounds, gyms/leisure centres, public swimming pools and public open spaces).

Results: A greater proportion of urban areas had a fast-food restaurant and gym/leisure centre present while more rural areas contained a supermarket and public swimming pool. All amenities examined (with the exception of swimming pools) were more numerous per km² in urban areas, however rural areas had a greater number of all supermarkets, other supermarkets, playgrounds, swimming pools and public open area per '000 population.

Conclusion: Although opportunities to engage in healthy eating and physical activity exist in many rural areas, a lower density per km² suggests a greater travel distance may be required to reach these.

Cohort profile : The resilience for eating and activity despite inequality (READI) study

The Resilience for Eating and Activity Despite Inequality (READI) cohort was established to address the following two key aims: to investigate the pathways (personal, social and structural) by which socio-economic disadvantage influences lifestyle choices associated with obesity risk (physical inactivity, poor dietary choices) and to explore mechanisms underlying ‘resilience’ to obesity risk in socio-economically disadvantaged women and children. A total of 4349 women aged 18–46 years and 685 children aged 5–12 years were recruited from 80 socio-economically disadvantaged urban and rural neighbourhoods of Victoria, Australia, and provided baseline (T1: 2007–08) measures of adiposity, physical activity, sedentary and dietary behaviours; socio-economic and demographic factors; and psychological, social and perceived environmental factors that might impact on obesity risk. Audits of the 80 neighbourhoods were undertaken at baseline to provide objective neighbourhood environmental data. Three-year follow-up data (2010–11) have recently been collected from 1912 women and 382 children. Investigators welcome enquiries regarding data access and collaboration.

Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Barriers to avoiding fast-food consumption in an environment supportive of unhealthy eating

Objective
To investigate factors (ability, motivation and the environment) that act as barriers to limiting fast-food consumption in women who live in an environment that is supportive of poor eating habits.

Design
Cross-sectional study using self-reports of individual-level data and objectively measured environmental data. Multilevel logistic regression was used to assess factors associated with frequency of fast-food consumption.

Setting
Socio-economically disadvantaged areas in metropolitan Melbourne, Australia.

Subjects
Women (n 932) from thirty-two socio-economically disadvantaged neighbourhoods living within 3 km of six or more fast-food restaurants. Women were randomly sampled in 2007–2008 as part of baseline data collection for the Resilience for Eating and Activity Despite Inequality (READI) study.

Results
Consuming low amounts of fast food was less likely in women with lower perceived ability to shop for and cook healthy foods, lower frequency of family dining, lower family support for healthy eating, more women acquaintances who eat fast food regularly and who lived further from the nearest supermarket. When modelled with the other significant factors, a lower perceived shopping ability, mid levels of family support and living further from the nearest supermarket remained significant. Among those who did not perceive fruits and vegetables to be of high quality, less frequent fast-food consumption was further reduced for those with the lowest confidence in their shopping ability.

Conclusions
Interventions designed to improve women's ability and opportunities to shop for healthy foods may be of value in making those who live in high-risk environments better able to eat healthily.