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Integration of high-dimensional tumor gene expression data with clinicopathological data can increase our understanding of disease diversity, enable retrospective patient stratification, and identify new potential biomarkers and therapeutic targets. Using a systems biology approach, we provide a holistic overview of gene co-expression networks in head and neck squamous cell carcinomas (HNSCC). Weighted gene co-expression network analysis of HNSCC RNA sequencing data from 519 patients from The Cancer Genome Atlas (TCGA) was used to determine correlates of 5-year survival, using regression tree-based optimal threshold calculations. Survival-associated gene sets were transformed to gene set scores that were assessed for correlation with clinicopathological data. We identified 8 gene co-expression modules for HNSCC tumors, each of which contained co-expressed genes associated significantly with 5-year survival. Survival-associated co-expression gene signatures correlated dominantly with tumor HPV and p16 status. Network analysis identified that survival was associated with signaling networks of infection, immunity, epithelial-mesenchymal transition (EMT), hypoxia, glycolysis, focal adhesion, extracellular matrix, MYC signaling, autophagy and transcriptional regulation. EMT-associated gene signatures were expressed dominantly in fibroblasts, and cancer-associated fibroblasts were inversely correlated with immune activity. Interestingly, a high Immune Suppression Score based on expression of 21 genes associated with immune inhibition and including immune checkpoints, cytokines and regulatory T cell factors, was also associated with increased survival probability, and was significantly higher in HPV+ HNSCC. Networks associated with HNSCC survival were further associated with survival in cervical cancer, melanoma and lung cancer. This study defines 5129 genes associated with HNSCC survival, organized into co-expressed networks, their correlation with clinicopathological dat

OBJECTIVE: To identify whether supportive care needs vary according to remoteness and area-level socio-economic status and to identify the combinations of socio-demographic, area-level and health factors that are associated with poorer quality of life, psychological distress and severity of unmet supportive care needs. METHODS: Cross sectional data was collected from women with a breast cancer diagnosis (n = 2635) in Queensland, Australia, through a telephone survey including socio-demographic, health, psychosocial and supportive care needs measures. Hierarchical regression and cluster analyses were applied to assess the predictors of unmet need and psychosocial outcomes and to identify socio-demographic and health status profiles of women, comparing their level of unmet needs and psychosocial outcomes. RESULTS: Women living in outer regional areas reported the highest severity of unmet need in the patient care domain. Greater unmet need for health systems and information and patient care was also evident for those in moderately and most disadvantaged areas. Three clusters were identified reflecting (1) older women with poorer health and lower education (19%); (2) younger educated women with better health and private insurance (61%); and (3) physically active women with localised cancer who had completed treatment (20%). Poorer outcomes were evident in the first two of these clusters. CONCLUSIONS: This better understanding of the combinations of characteristics associated with poorer psychosocial outcomes and higher unmet need can be used to identify women with higher supportive care needs early and to target interventions.

Interrelationships between neighborhood walkability, area disadvantage, and crime may contribute to the inconsistent associations between crime and walking. We examined associations between crime and walking, and tested for differences by neighborhood disadvantage while addressing these additional complexities. Participants ( n = 6,680) from 200 neighborhoods spanning the most and least disadvantaged in Brisbane, Australia, completed a questionnaire and objective measures were generated for the individual-level 1,000-m neighborhood. Multilevel models examined associations between crime (perceived and objective) and walking (recreational and transport), and interactions tested for differences by neighborhood disadvantage. High perceived crime was associated with reduced odds of transport walking, whereas high objective crime was associated with increased odds of transport walking. Patterns did not differ by neighborhood disadvantage. In disadvantaged neighborhoods, the “negative” criminogenic attributes were insufficient to outweigh the “positive” walkability attributes, producing similar walking patterns to advantaged neighborhoods where residents were dislocated from local destinations but buffered from crime.

OBJECTIVES: Cross-sectional studies have found some built environmental attributes to be associated with residents' lower levels of mobility (functional capacity to walk outside the home). However, less is known about what environmental attributes are related to mobility decline. This longitudinal study examined area-level associations of specific environmental attributes with mid-to-older aged adults' changes in walking mobility. METHODS: Data collected from 4,088 adults (aged 46-71 years at baseline) who participated in a cohort study in Brisbane, Australia were used. The outcome was the change in self-reported mobility score (SF-36) from 2013 to 2016, which were aggregated at the neighborhood (N = 156) and suburb (N = 99) levels, due to the known lack of sensitivity in SF-36 subscales to individual changes. Linear regression analysis examined associations of mobility change with seven environmental attributes measured at baseline (residential density, intersection density, land use mix, density of walking/bike paths, park density, bus stop density, density of social incivilities), adjusting for confounding variables. RESULTS: Participants on average reported 4% of mobility decline during the 3-year study period. It was found that greater land use diversity was consistently associated with less decline in walking mobility, while greater density of social incivilities was associated with more decline in walking mobility. The latter finding was significant only at the neighborhood level. No consistent associations were observed for residential density, intersection density, density of walking/bike paths, park density, and bus stop density. DISCUSSION: Our findings suggest that mid-to-older aged adults who live in areas with lower land use diversity and more social incivilities may be at risk of developing mobility limitations. Recommended policies to slow residents' mobility decline and to achieve aging in place include improving these environmental attributes where

Built environment attributes may be related to cardio-metabolic diseases (e.g. type 2 diabetes, heart disease and stroke) and their risk factors, potentially by influencing residents' physical activity. However, existing literature reviews on the built environment and health for the most part focus on obesity as the outcome and rely on cross-sectional studies. This systematic review synthesized current evidence on longitudinal relationships between built environment attributes and cardio-metabolic health outcomes among adults and on the potential mediating role of physical inactivity. By searching eight databases for peer-reviewed journal articles published in the English language between January 2000 and July 2016, the review identified 36 articles. A meta-analysis method, weighted Z-test, was used to quantify the strength of evidence by incorporating the methodological quality of the studies. We found strong evidence for longitudinal relationships of walkability with obesity, type 2 diabetes and hypertension outcomes in the expected direction. There was strong evidence for the impact of urban sprawl on obesity outcomes. The evidence on potential mediation by physical activity was inconclusive. Further longitudinal studies are warranted to examine which specific built environment attributes influence residents' cardio-metabolic health outcomes and how physical inactivity may be involved in these relationships.

Within a city, gender differences in walking for recreation (WfR) vary significantly across neighbourhoods, although the reasons remain unknown. This cross-sectional study investigated the contribution of the social environment (SE) to explaining such variation, using 2009 data from the How Areas in Brisbane Influence healTh and AcTivity (HABITAT) study, including 7866 residents aged 42-67 years within 200 neighbourhoods in Brisbane, Australia (72.6% response rate). The analytical sample comprised 200 neighbourhoods and 6643 participants (mean 33 per neighbourhood, range 8-99, 95% CI 30.6-35.8). Self-reported weekly minutes of WfR were categorised into 0 and 1-840 mins. The SE was conceptualised through neighbourhood-level perceptions of social cohesion, incivilities and safety from crime. Analyses included multilevel binomial logistic regression with gender as main predictor, adjusting for age, socioeconomic position, residential self-selection and neighbourhood disadvantage. On average, women walked more for recreation than men prior to adjustment for covariates. Gender differences in WfR varied significantly across neighbourhoods, and the magnitude of the variation for women was twice that of men. The SE did not explain neighbourhood differences in the gender-WfR relationship, nor the between-neighbourhood variation in WfR for men or women. Neighbourhood-level factors seem to influence the WfR of men and women differently, with women being more sensitive to their environment, although Brisbane's SE did not seem such a factor.

Background Population densities of many cities are increasing rapidly, with the potential for impacts on cardiovascular health. This longitudinal study examined the potential impact of population-density increases in urban areas (urban densification) on cardiovascular risk markers among Australian adults. Methods and Results Data were from the Australian Diabetes, Obesity and Lifestyle Study, in which adult participants' cardiovascular risk markers were collected in 3 waves (in 1999-2000, 2004-2005, and 2011-2012). We included 2354 participants with a mean age of 51 years at baseline who did not change their residence during the study period. Outcomes were 12-year changes in waist circumference, weight, systolic and diastolic blood pressure, fasting and 2-hour postload plasma glucose, high-density lipoprotein cholesterol, and triglycerides. The exposure was neighborhood population densification, defined as 12-year change in population density within a 1-km radius buffer around the participant's home. Multilevel linear growth models, adjusting for potential confounders, were used to examine the relationships. Each 1% annual increase in population density was related with smaller increases in waist circumference (b=-0.043 cm/y; 95% CI, -0.065 to -0.021 [P<0.001]), weight (b=-0.019 kg/y; 95% CI, -0.039 to 0.001 [P=0.07]), and high-density lipoprotein cholesterol (b=-0.035 mg/dL per year; 95% CI, -0.067 to -0.002 [P=0.04]), and greater increases in diastolic blood pressure (b=0.032 mm Hg/y; 95% CI, -0.004 to 0.069 [P=0.08]). Conclusions Our findings suggest that, at least in the context of Australia, urban densification may be protective against obesity risk but may have adverse effects on blood lipids and blood pressure. Further research is needed to understand the mechanisms through which urban densification influences cardiovascular health.

Built environment attributes may be related to cardio-metabolic diseases (e.g. type 2 diabetes, heart disease and stroke) and their risk factors, potentially by influencing residents' physical activity. However, existing literature reviews on the built environment and health for the most part focus on obesity as the outcome and rely on cross-sectional studies. This systematic review synthesized current evidence on longitudinal relationships between built environment attributes and cardio-metabolic health outcomes among adults and on the potential mediating role of physical inactivity. By searching eight databases for peer-reviewed journal articles published in the English language between January 2000 and July 2016, the review identified 36 articles. A meta-analysis method, weighted Z-test, was used to quantify the strength of evidence by incorporating the methodological quality of the studies. We found strong evidence for longitudinal relationships of walkability with obesity, type 2 diabetes and hypertension outcomes in the expected direction. There was strong evidence for the impact of urban sprawl on obesity outcomes. The evidence on potential mediation by physical activity was inconclusive. Further longitudinal studies are warranted to examine which specific built environment attributes influence residents' cardio-metabolic health outcomes and how physical inactivity may be involved in these relationships.

BACKGROUND: Societies face the challenge of keeping people active as they age. Walkable neighborhoods have been associated with physical activity, but more rigorous analytical approaches are needed. OBJECTIVES: We used longitudinal data from adult residents of Brisbane, Australia (40-65 years of age at baseline) to estimate effects of changes in neighborhood characteristics over a 6-y period on the likelihood of walking for transport. METHODS: Analyses included 2,789-9,747 How Areas Influence Health and Activity (HABITAT) cohort participants from 200 neighborhoods at baseline (2007) who completed up to three follow-up questionnaires (through 2013). Principal components analysis was used to derive a proxy measure of walkability preference. Environmental predictors were changes in street connectivity, residential density, and land use mix within a one-kilometer network buffer. Associations with any walking and minutes of walking were estimated using logistic and linear regression, including random effects models adjusted for time-varying confounders and a measure of walkability preference, and fixed effects models of changes in individuals to eliminate confounding by time-invariant characteristics. RESULTS: Any walking for transport (vs. none) was increased in association with an increase in street connectivity (+10 intersections, fixed effects OR=1.19; 95% confidence interval (CI): 1.07, 1.32), residential density (+5 dwellings/hectare, OR=1.10; 95% CI: 1.05, 1.15), and land-use mix (10% increase, OR=1.12; 95% CI: 1.00, 1.26). Associations with minutes of walking were positive based on random effects models, but null for fixed effects models. The association between land-use mix and any walking appeared to be limited to participants in the highest tertile of increased street connectivity (fixed effects OR=1.17; 95% CI: 0.99, 1.35 for a 1-unit increase in land-use mix; interaction p-value=0.05). CONCLUSIONS: Increases in street connectivity, residential density, and l

Natural experiments, such as longitudinal observational studies that follow-up residents as they relocate, provide a strong basis to infer causation between the neighborhood environment and health. In this study, we examined whether changes in the level of neighborhood disadvantage were associated with changes in body mass index (BMI) after residential relocation. This analysis included data from 928 residents who relocated between 2007 and 2013, across 4 waves of the How Areas in Brisbane Influence Health and Activity (HABITAT) study in Brisbane, Australia. Neighborhood disadvantage was measured using a census-derived composite index. For individual-level data, participants self-reported their height, weight, education, occupation, and household income. Data were analyzed using multilevel, hybrid linear models. Women residing in less disadvantaged neighborhoods had a lower BMI, but there was no association among men. Neighborhood disadvantage was not associated with within-individual changes in BMI among men or women when moving to a new neighborhood. Despite a growing body of literature suggesting an association between neighborhood disadvantage and BMI, we found this association may not be causal among middle-aged and older adults. Observing associations between neighborhood socioeconomic disadvantage and BMI over the life course, including the impact of residential relocation at younger ages, remains a priority for future research.

BACKGROUND: Few studies have examined the causal relationship between transport mode and body mass index (BMI). METHODS: We examined between-person differences and within-person changes in BMI by transport mode over four time points between 2007 and 2013. Data were from the How Areas in Brisbane Influence HealTh and AcTivity project, a population-representative study of persons aged 40-65 in 2007 (baseline) residing in 200 neighbourhoods in Brisbane, Australia. The analytic sample comprised 9931 respondents who reported on their main transport for all travel purposes (work-related and non-work-related). Transport mode was measured as private motor vehicle (PMV), public transport, walking and cycling. Self-reported height and weight were used to derive BMI. Sex-specific analyses were conducted using multilevel hybrid regression before and after adjustment for time-varying and time-invariant confounders. RESULTS: Independent of transport mode and after adjustment for confounders, average BMI increased significantly and linearly across the four time points for both men and women. Men and women who walked or cycled had a significantly lower BMI than their counterparts who used a PMV. BMI was nearly always lower during the time men and women walked or cycled than when they used a PMV; however, few statistically significant differences were observed. For women, BMI was significantly higher during the time they used public transport than when using a PMV. CONCLUSION: The findings suggest a causal association between transport mode and BMI and support calls from health authorities to promote walking and cycling for transport as a way of incorporating physical activity into everyday life to reduce the risk of chronic disease.

Cities that support cycling for transportation reap many public health benefits. However, the prevalence of this mode of transportation is low in Latin American countries and the association with facilities such as bike paths and train/subway stations have not been clarified. We conducted a cross-sectional analysis of the relationship between bike paths, train/subway stations and cycling for transportation in adults from the city of Sao Paulo. We used data from the Sao Paulo Health Survey (n = 3145). Cycling for transportation was evaluated by a questionnaire and bike paths and train/subway stations were geocoded using the geographic coordinates of the adults' residential addresses in 1500-m buffers. We used multilevel logistic regression, taking account of clustering by census tract and households. The prevalence of cycling for transportation was low (5.1%), and was more prevalent in males, singles, those active in leisure time, and in people with bicycle ownership in their family. Cycling for transportation was associated with bike paths up to a distance of 500 m from residences (OR (Odds Ratio) = 2.54, 95% CI (Confidence interval) 1.16-5.54) and with the presence of train/subway stations for distances >500 m from residences (OR = 2.07, 95% CI 1.10-3.86). These results are important to support policies to improve cycling for transportation in megacities such as Sao Paulo.

With the increase of unmarried cohabitation a growing body of research examines health differences between married and cohabiting people, but few studies investigate what happens when relationships end. While cohabitation offers some similar health advantages to marriage, typically cohabitants have been together less time, are less likely to have children or to have shared finances. Therefore separating from cohabitation may be less difficult than marriage. We compare Switzerland and Australia because the Swiss are more conservative in relationship formation and dissolution, where Swiss cohabitations are more serious and marriages more stable than in Australia. There are also important policy differences, where long-term cohabitants have the same legal entitlements as married couples in Australia, but not in Switzerland. To examine country differences in the health consequences of separation for cohabitants and married people we use 16 waves of the Swiss Household Panel (SHP) and 14 Waves of the Household, Income and Labour Dynamics in Australia study (HILDA). Our sample includes respondents aged between 18 and 65 in cohabiting or marital relationships. Our dependent variables measure negative feelings, positive feelings and self-rated health. Using fixed effects regression models with lagged marital status measures we find that overall separation from marriage produces greater negative feelings and fewer positive feelings than separation from cohabitation, although differences vary by gender. Relationship dissolution had a stronger association with feelings compared to self-rated health. No clear country differences were found.

Despite a body of evidence on the relationship between neighborhood socioeconomic disadvantage and body mass index (BMI), few studies have examined this relationship over time among ageing populations. This study examined associations between level of neighborhood socioeconomic disadvantage and the rate of change in BMI over time. The sample included 11,035 participants aged between 40 and 65years at baseline from the HABITAT study, residing in 200 neighborhoods in Brisbane, Australia. Data were collected biennially over four waves from 2007 to 2013. Self-reported height and weight were used to calculate BMI, while neighborhood disadvantage was measured using a census-based composite index. All models were adjusted for age, education, occupation, and household income. Analyses were conducted using multilevel linear regression models. BMI increased over time at a rate of 0.08kg/m2 (95% CI 0.02, 0.13) and 0.17kg/m2 (95% CI 0.11, 0.29) per wave for men and women respectively. Both men and women residing in the most disadvantaged neighborhoods had a higher average BMI than their counterparts living in the least disadvantaged neighborhoods. There were no evident differences in the rate of BMI change over time by level of neighborhood disadvantage. The findings suggest that by mid-older age, the influence of neighborhood socioeconomic conditions over time on BMI may have already played out. Future research should endeavor to identify the genesis of neighborhood socioeconomic inequalities in BMI, the determinants of these inequalities, and then suitable approaches to intervening.

OBJECTIVES: To examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as 'item missing'. DESIGN: Observational study of longitudinal data. SETTING: Residents of Brisbane, Australia. PARTICIPANTS: 6901 people aged 40-65 years in 2007. MATERIALS AND METHODS: We used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants' characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey. RESULTS: Four per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave. CONCLUSIONS: Examining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data.

Access to public open space is important to increase leisure-time walking (LTW) in high-income countries, but there is little evidence in middle-income countries. We conducted a cross-sectional analysis to examine the relationship between LTW and the presence of different public open spaces (parks, bike paths, and squares) and the mix of these recreational destinations near the homes of adults participating in the Sao Paulo Health Survey (n = 3145). LTW was evaluated by a questionnaire. We delineated buffers (500, 1000, and 1500 m) from the geographic coordinates of the adults' residential addresses using a geographic information system. We used multilevel logistic regression taking account of clustering by census tracts and households, and with adjustment for social, demographics, and health characteristics. The main results showed that the presence of at least two recreational destinations within a 500-m buffer of participants' homes were associated with an increased odds of LTW compared with no destinations present (OR = 1.65; 95% CI 1.09-2.55). No associations were found for destinations further away. These results support actions outlined in the new urban plan for Sao Paulo city and could be used to highlight the importance access to a mix of public open spaces to promote physical activity in megacities of middle-income countries.

© 2017 Elsevier Ltd The relationship between features of the neighbourhood built environment and early child development was investigated using area-level data from the Australian Early Development Census. Overall 9.0% of children were developmentally vulnerable on the Physical Health and Well-being domain, 8.1% on the Social Competence domain and 8.1% on the Emotional Maturity domain. After adjustment for socio-demographic factors, Local Communities with the highest quintile of home yard space had significantly lower odds of developmental vulnerability on the Emotional Maturity domain. Residing in a Local Community with fewer main roads was associated with a decrease in the proportion of children developmentally vulnerable on the Social Competence domain. Overall, sociodemographic factors were more important than aspects of the neighbourhood physical environment for explaining variation between Local Communities in the developmental vulnerability of children.

BACKGROUND: Despite growing international migration and documented ethnic differences in overweight and obesity in developed countries, no research has described the epidemiology of immigrant overweight and obesity at a national level in Australia, a country where immigrants comprise 28.1 % of the population. The aim of this study was to examine ethnic differences in body mass index (BMI) and overweight/obesity in Australia and the influence of acculturation on bodyweight among Australian immigrants. METHODS: Data from the national Household Income and Labour Dynamics in Australia (HILDA) survey were used to examine mean BMI and odds of overweight/obesity comparing immigrants (n = 2 997) with Australian born (n = 13 047). Among immigrants, acculturation differences were examined by length of residence in Australia and age at migration. Data were modelled in a staged approach using multilevel linear and logistic regression, controlling for demographic and socioeconomic variables. RESULTS: Relative to Australian born, men from North Africa/Middle East and Oceania regions had significantly higher BMIs, and men from North West Europe, North East Asia and Southern and Central Asia had significantly lower BMIs. Among women, the majority of foreign born groups had significantly lower BMIs compared with Australian born. Male and female immigrants living in Australia for 15 years or more had significantly higher BMIs and increased odds of being overweight/obese respectively, compared with immigrants living in Australia for less than 5 years. Male immigrants arriving as adolescents were twice more likely to be overweight/obese and had significantly higher BMIs than immigrants who arrived as adults. Male and female immigrants who arrived as children (≤11 years) had significantly higher odds of adult overweight/obesity and BMIs. CONCLUSIONS: This study provides evidence of ethnic differences in overweight and obesity in Australia with male immigrants from North Africa/Middle Ea

Delays in diagnosing breast cancer (BC) can lead to poorer outcomes. We investigated factors related to the diagnostic interval in a population-based cohort of 3202 women diagnosed with BC in Queensland, Australia. Interviews ascertained method of detection and dates of medical/procedural appointments, and clinical information was obtained from medical records. Time intervals were calculated from self-recognition of symptoms (symptom-detected) or mammogram (screen-detected) to diagnosis (diagnostic interval (DI)). The cohort included 1560 women with symptom-detected and 1642 with screen-detected BC. Symptom-detected women had higher odds of DI of >60 days if they were Indigenous (OR = 3.12, 95% CI = 1.40, 6.98); lived in outer regional (OR = 1.50, 95% CI = 1.09, 2.06) or remote locations (OR = 2.46, 95% CI = 1.39, 4.38); or presented with a "non-lump" symptom (OR = 1.84, 95% CI = 1.43, 2.36). For screen-detected BC, women who were Indigenous (OR = 2.36, 95% CI = 1.03, 5.80); lived in remote locations (OR = 2.35, 95% CI = 1.24, 4.44); or disadvantaged areas (OR = 1.69, 95% CI = 1.17, 2.43) and attended a public screening facility (OR = 2.10, 95% CI = 1.40, 3.17) had higher odds of DI > 30 days. Our study indicates a disadvantage in terms of DI for rural, disadvantaged and Indigenous women. Difficulties in accessing primary care and diagnostic services are evident. There is a need to identify and implement an efficient and effective model of care to minimize avoidable longer diagnostic intervals.

INTRODUCTION: Walking as regular physical activity (PA) is central to healthy aging, and environments influence walking. Multilevel neighborhood-based studies that only report average (fixed-effect) walking differences for gender and age implicitly assume that neighborhood environments influence the walking behavior of men and women, and younger and older persons, similarly. This study tests this assumption by examining whether gender and age differences in walking for transport (WfT) and walking for recreation (WfR) are similar or different across neighborhoods. METHODS: This paper used data from the HABITAT multilevel study, with 7,866 participants aged 42-68 years in 2009 living in 200 neighborhoods in Brisbane, Australia. Respondents reported minutes spent WfT and WfR in the previous week, categorized as: none (0 mins), low (1-59mins), moderate (60-149mins) and high (≥ 150 mins). Multilevel multinomial logistic models were used to estimate average differences in walking by gender and age, followed by random coefficients to examine neighborhood variation in these individual-level relationships. RESULTS: On average, women were more likely to engage in WfR at moderate and high levels (no gender differences found in WfT); and older persons were less likely to do WfT and more likely to do high levels of WfR. These average (Brisbane-wide) relationships varied significantly across neighborhoods. CONCLUSION: Relationships between gender and walking, and age and walking, are not the same in all neighborhoods, (i.e. the Brisbane average conceals important information) suggesting that neighborhood-level factors differentially influence the walking behaviors of men and women and younger and older persons. Identifying these factors should be a priority for future research.

This study examined associations between objective environmental attributes and, separately, transport (TC) and recreational cycling (RC). Environmental attributes were more strongly associated with TC than RC. Distances to areas with the best bicycle infrastructure and urban amenities may be key environmental attributes influencing TC but not RC. Government investments in bicycle infrastructure within inner Brisbane appear to have resulted in more TC than in outer areas and to appeal to residents of both the most and least disadvantaged neighbourhoods. Extending this infrastructure to residents living in disadvantaged and advantaged neighbourhoods outside the CBD could expand TC participation.

AIM: Liveable communities create the conditions to optimise health and wellbeing outcomes in residents by influencing various social determinants of health - for example, neighbourhood walkability and access to public transport, public open space, local amenities, and social and community facilities. This study will develop national liveability indicators that are (a) aligned with state and federal urban policy, (b) developed using national data (where available), (c) standard and consistent over time, (d) suitable for monitoring progress towards creating more liveable, equitable and sustainable communities, (e) validated against selected noncommunicable disease risk behaviours and/or health outcomes, and (f) practical for measuring local, national and federal built environment interventions. STUDY TYPE: Protocol. METHOD: Over two years, the National Liveability Study, funded through The Australian Prevention Partnership Centre (TAPPC), will develop and validate a national set of spatially derived built environment liveability indicators related to noncommunicable disease risk behaviours and/or health outcomes, informed by a review of relevant policies in selected Australian state and territory governments. To create national indicators, we will compare measures developed using national data with finer-grained state-level data, which have been validated against a range of outcomes. Finally, we will explore the creation of a national database of built environment spatial indicators. RESULTS: A national advisory group comprising stakeholders in state and federal government, federal nongovernment organisations and state-based technical working groups located in the ACT, Victoria, NSW, Queensland and WA has been established; a policy analysis is under way and work programs are being prepared. CONCLUSION: This project seeks to build the capacity for built environment and health systems research by developing national indicators to monitor progress towards creating health

BACKGROUND: Unlike leisure time physical activity, knowledge of the socioeconomic determinants of active transport is limited, research on this topic has produced mixed and inconsistent findings, and it remains unknown if peoples' engagement in active transport declines as they age. This longitudinal study examined relationships between neighbourhood disadvantage, individual-level socioeconomic position and walking for transport (WfT) during mid- and early old-age (40 - 70 years). Three questions were addressed: (i) which socioeconomic groups walk for transport, (ii) does the amount of walking change over time as people age, and (iii) is the change socioeconomically patterned? METHODS: The data come from the HABITAT study of physical activity, a bi-annual multilevel longitudinal survey of 11,036 residents of 200 neighbourhoods in Brisbane, Australia. At each wave (2007, 2009 and 2011) respondents estimated the duration (minutes) of WfT in the previous 7 days. Neighbourhood disadvantage was measured using a census-derived index comprising 17 different socioeconomic components, and individual-level socioeconomic position was measured using education, occupation, and household income. The data were analysed using multilevel mixed-effects logistic and linear regression. RESULTS: The odds of being defined as a 'never walker' were significantly lower for residents of disadvantaged neighbourhoods, but significantly higher for the less educated, blue collar employees, and members of lower income households. WfT declined significantly over time as people aged and the declines were more precipitous for older persons. Average minutes of WfT declined for all neighbourhoods and most socioeconomic groups; however, the declines were steeper for the retired and members of low income households. CONCLUSIONS: Designing age-friendly neighbourhoods might slow or delay age-related declines in WfT and should be a priority. Steeper declines in WfT among residents of low income households

BACKGROUND: Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. METHODS: Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20-84 years diagnosed during 1997-2007 from Queensland, Australia. RESULTS: Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. CONCLUSIONS: With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from interna