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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/m 2 (95% CI 0.02, 0.13) and 0.17kg/m 2 (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., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Introduction: Understanding associations between physical function and neighborhood disadvantage may provide insights into which interventions might best contribute to reducing socioeconomic inequalities in health. This study examines associations between neighborhood-disadvantage, individual-level socioeconomic position (SEP) and physical function from a multilevel perspective., Methods: Data were obtained from the HABITAT multilevel longitudinal (2007-13) study of middle-aged adults, using data from the fourth wave (2013). This investigation included 6004 residents (age 46-71years) of 535 neighborhoods in Brisbane, Australia. Physical function was measured using the PF-10 (0-100), with higher scores indicating better function. The data were analyzed using multilevel linear regression and were extended to test for cross-level interactions by including interaction terms for different combinations of SEP (education, occupation, household income) and neighborhood disadvantage on physical function., Results: Residents of the most disadvantaged neighborhoods reported significantly lower physical function (men: β -11.36 95% CI -13.74, -8.99; women: β -11.41 95% CI -13.60, -9.22). These associations remained after adjustment for individual-level SEP. Individuals with no post-school education, those permanently unable to work, and members of the lowest household income had significantly poorer physical function. Cross-level interactions suggested that the relationship between household income and physical function is different across levels of neighborhood disadvantage for men; and for education and occupation for women., Conclusion: Living in a disadvantaged neighborhood was negatively associated with physical function after adjustment for individual-level SEP. These results may assist in the development of policy-relevant targeted interventions to delay the rate of physical function decline at a community-level., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: This study aims to determine if neighbourhood psychosocial characteristics contribute to inequalities in smoking among residents from neighbourhoods of differing socioeconomic disadvantage., Methods: This cross-sectional study includes 11,035 residents from 200 neighbourhoods in Brisbane, Australia in 2007. Self-reported measures were obtained for smoking and neighbourhood psychosocial characteristics (perceptions of incivilities, crime and safety, and social cohesion). Neighbourhood socioeconomic disadvantage was measured using a census-derived index. Data were analysed using multilevel logistic regression random intercept models., Results: Smoking was associated with neighbourhood disadvantage; this relationship remained after adjustment for individual-level socioeconomic position. Area-level perceptions of crime and safety and social cohesion were not independently associated with smoking, and did not explain the higher prevalence of smoking in disadvantaged areas; however, perceptions of incivilities showed an independent effect., Conclusions: Some neighbourhood psychosocial characteristics seem to contribute to the higher rates of smoking in disadvantaged areas., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The aim of this study was to examine whether takeaway food consumption mediated (explained) the association between socioeconomic position and body mass index (BMI). A postal-survey was conducted among 1500 randomly selected adults aged between 25 and 64years in Brisbane, Australia during 2009 (response rate 63.7%, N=903). BMI was calculated using self-reported weight and height. Participants reported usual takeaway food consumption, and these takeaway items were categorised into "healthy" and "less healthy" choices. Socioeconomic position was ascertained by education, household income, and occupation. The mean BMI was 27.1kg/m(2) for men and 25.7kg/m(2) for women. Among men, none of the socioeconomic measures were associated with BMI. In contrast, women with diploma/vocational education (β=2.12) and high school only (β=2.60), and those who were white-collar (β=1.55) and blue-collar employees (β=2.83) had significantly greater BMI compared with their more advantaged counterparts. However, household income was not associated with BMI. Among women, the consumption of "less healthy" takeaway food mediated BMI differences between the least and most educated, and between those employed in blue collar occupations and their higher status counterparts. Decreasing the consumption of "less healthy" takeaway options may reduce socioeconomic inequalities in overweight and obesity among women but not men., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

A major priority for cancer control agencies is to reduce geographical inequalities in cancer outcomes. While the poorer breast cancer survival among socioeconomically disadvantaged women is well established, few studies have looked at the independent contribution that area- and individual-level factors make to breast cancer survival. Here, we examine relationships between geographic remoteness, area-level socioeconomic disadvantage and breast cancer survival after adjustment for patients' socio-demographic characteristics and stage at diagnosis. Multilevel logistic regression and Markov chain Monte Carlo simulation were used to analyze 18,568 breast cancer cases extracted from the Queensland Cancer Registry for women aged 30-70 years diagnosed between 1997 and 2006 from 478 Statistical Local Areas in Queensland, Australia. Independent of individual-level factors, area-level disadvantage was associated with breast cancer survival (P = 0.032). Compared to women in the least disadvantaged quintile (quintile 5), women diagnosed while resident in one of the remaining four quintiles had significantly worse survival (OR 1.23, 1.27, 1.30, 1.37 for quintiles 4, 3, 2, and 1, respectively). Geographic remoteness was not related to lower survival after multivariable adjustment. There was no evidence that the impact of area-level disadvantage varied by geographic remoteness. At the individual-level, Indigenous status, blue collar occupations and advanced disease were important predictors of poorer survival. A woman's survival after a diagnosis of breast cancer depends on the socio-economic characteristics of the area where she lives, independently of her individual-level characteristics. It is crucial that the underlying reasons for these inequalities be identified to appropriately target policies, resources and effective intervention strategies.

Objective: To examine socio-economic differences in weight-control behaviours (WCB) and barriers to weight control., Design: A cross-sectional study., Setting: Data were obtained by means of a postal questionnaire., Subjects: A total of 1013 men and women aged 45-60 years residing in Brisbane, Australia (69·8 % response rate)., Results: Binary and multinomial logistic regression analyses were performed, adjusted for age, gender and BMI. Socio-economically disadvantaged groups were less likely to engage in weight control (OR for lowest income quartile = 0·60, 95 % CI 0·39, 0·94); among those who engaged in weight control, the disadvantaged group had a likelihood of 0·52 (95 % CI 0·30, 0·90) of adopting exercise strategies, including moderate (OR = 0·56, 95 % CI 0·33, 0·96) and vigorous (OR = 0·47, 95 % CI 0·25, 0·89) physical activities, compared with their more-advantaged counterparts. However, lower socio-economic groups were more likely to decrease their sitting time to control their weight compared with their advantaged counterparts (OR for secondary school or lower education = 1·78, 95 % CI 1·11, 2·84). They were also more likely to believe that losing weight was expensive, not of high priority, required a lot of cooking skills and involved eating differently from others in the household., Conclusions: Marked socio-economic inequalities existed with regard to engaging in WCB, the type of weight-control strategies used and the perceived barriers to weight control; these differences are consistent with socio-economic gradients in weight status. These factors may need to be included in health promotion strategies that address socio-economic inequalities in weight status, as well as inequalities in weight-related health outcomes.

Aim: To examine associations between individual-, household- and neighbourhood-level socioeconomic position (SEP) and harmful alcohol consumption., Method: Adults aged 18-76 residing in 50 neighbourhoods in Melbourne completed a postal questionnaire (n= 2349, 58.7% response rate). Alcohol-related behaviours were classified by risk of short- and long-term harm. Individual-, household- and neighbourhood-level SEP were ascertained by education, household income and proportion of low-income households, respectively. The association were examined by multi-level logistic regression., Results: Participants lower education or household income were less likely to consume alcohol frequently compared to their more-advantaged counterparts. Lower-educated men were more likely to be at risk of short-term harm [OR 1.75 (1.23 - 2.48)]. Low-income women were less likely to be at risk of short-term harm [OR 0.44 (0.23 - 0.81)]. Neighbourhood disadvantage was not associated with alcohol consumption., Conclusion: Men and women from socioeconomically advantaged backgrounds were more frequent consumers of alcohol, whereas their disadvantaged counterparts drank less frequently but in greater quantities on each drinking occasion., Implications: Socioeconomic disadvantage at the individual and household levels may be an important determinant of alcohol consumption among Australian adults., (© 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.)

Objective: To examine associations between area and individual socio-economic characteristics and premature cancer mortality using multilevel analysis., Methods: We modeled cancer mortality among 25-64-year-old men and women (n = 16,340) between 1998 and 2000 in Australia. Socio-economic characteristics of Statistical Local Areas (n = 1,317) were measured using an Index of Relative Socio-economic Disadvantage (quintiles), and individual socio-economic position was measured by occupation (professionals, white and blue collar)., Results: After adjustment for within-area variation in age and occupation, the probability of premature cancer mortality was highest in the most disadvantaged areas for all-cancer mortality for men (RR 1.48 95% CI 1.35-1.63) and women (RR 1.30 95% CI 1.18-1.43) and for lung cancer mortality for men (1.91 95% CI 1.63-2.25) and women (1.51 95% CI 1.04-2.18). Men in blue collar occupations had a higher rate of cancer mortality (RR 1.57 95% CI 1.50-1.65) and lung cancer mortality (RR 2.31 95 % CI 2.09-2.56), whereas men in white collar occupations had a lower all-cancer mortality rate (RR 0.78 95% CI 0.72-0.85). Compared with professionals, women in white collar occupations had an all-cancer mortality rate that was lower (RR 0.85 95% CI 0.80-0.90). When deaths from breast cancer were excluded, women in blue collar occupations had a significantly higher all-cancer mortality rate than professionals (RR 1.12 95% CI 1.02-1.22)., Conclusions: Area disadvantage and individual socio-economic position were independently associated with premature cancer mortality, suggesting that interventions to reduce inequalities should focus on places and people.

This qualitative study explored how influences on recreational physical activity (RPA) were patterned by socioeconomic position. Face-to-face interviews were conducted with 10 males and 10 females in three socioeconomic groups (N = 60). Influences salient across all groups included previous opportunities, physical health. social assistance. safety. environmental aesthetics and urban design, physical and health benefits, and barriers of self-consciousness, low skill, and weather/time of year. Influences more salient to the high socioeconomic group included social benefits, achieving a balanced lifestyle, and the barrier of an unpredictable lifestyle. Influences more salient to the high and mid socioeconomic groups included efficacy, perceived need, activity demands, affiliation, emotional benefits, and the barrier of competing demands. Influences more salient to the low socioeconomic group included poor health and barriers of inconvenient access and low personal functioning. Data suggest that efforts to increase RPA in the population should include both general and socioeconomically targeted strategies.

Objectives: To estimate the smoking prevalence among parents of infants and examine these parents' socio-demographic characteristics., Method: The sample of all parents of infants (669 mother-father pairs, 90 single parents) was derived from the 1995 Australian Health Survey. Data were collected by face-to-face interview in the respondent's home. Socio-demographic measures include parent's age, family structure, age-left-school, highest post-school qualification, occupation, and family income., Results: The overall rate of smoking among parents was 28.9% (mothers 24.7%, fathers 33.7%). The lowest rate was observed among mothers with a post-school tertiary qualification (7.6%) and the highest among fathers aged 18-24 (49.0%). In 15.4% of two-parent families both parents smoked, but this rate differed markedly by family income (9.9% vs. 29.7% for high and low-income families respectively). Multiple logistic regression showed that parents who smoked were more likely to be young, minimally educated, employed in blue-collar occupations, and resident in low-income families., Conclusions and Implications: Infants in this sample who were exposed to parental smoking were likely to be at increased risk of experiencing higher mortality and morbidity for childhood conditions related to passive smoking; more likely to experience adverse health consequences in adulthood; and may themselves take up smoking in later life. The study results pose serious challenges to our tobacco control efforts and health interventions more generally. No single policy or strategy can adequately address the problem of parental smoking. We need macro/upstream approaches that deal with the degree of social and economic inequality in society, as well as more intermediate approaches that intervene at the level of communities, families and individuals.

Background: Socioeconomic disadvantage is associated with mental illness, yet its relationship with mental well-being is unclear. Mental well-being is defined as feeling good and functioning well. Benefits of mental well-being include reduced mortality, improved immune functioning and pain tolerance, and increased physical function, pro-social behaviour, and academic and job performance. This study aims to explore the relationship between individual socioeconomic position (SEP), neighbourhood disadvantage and mental well-being in mid-age adults.Methods: Multilevel modelling was used to analyse data collected from 7866 participants from the second (2009) wave of HABITAT (How Areas in Brisbane Influence healTh and activiTy), a longitudinal study (2007-2018) of adults aged 40-65 years living in Brisbane, Australia. Mental well-being was measured using the Warwick Edinburgh Mental Well-Being Scale (WEMWBS). Exposure measures were education, occupation, household income, and neighbourhood socioeconomic disadvantage.Results: The lowest MWB scores were observed for the least educated (β = - 1.22, 95%CI = - 1.74, - 0.71), those permanently unable to work (β = - 5.50, 95%CI = - 6.90, - 4.10), the unemployed (β = - 2.62, 95%CI = - 4.12, - 1.13), and members of low-income households (β = - 3.77, 95%CI = - 4.59, - 2.94). Residents of the most disadvantaged neighbourhoods had lower MWB scores than those living in the least disadvantaged neighbourhoods, after adjustment for individual-level SEP (β = - 0.96, 95%CI = - 1.66, - 0.28).Conclusions: Both individual-level SEP and neighbourhood disadvantage are associated with mental well-being although the association is stronger for individual-level SEP. This research highlights the need to address individual and neighbourhood-level socioeconomic determinants of mental well-being. [ABSTRACT FROM AUTHOR]

Background: Further development of high quality measures of neighborhood perceptions will require extensions and refinements to our existing approaches to reliability assessment. This study examined the test-retest reliability of perceptions of the neighborhood environment by socioeconomic status (SES). Methods: Test and retest surveys were conducted using a mail survey method with persons aged 40 to 65 years (n = 222, 78.2% response rate). SES was measured using the respondent's education level and the socioeconomic characteristics of their neighborhood of residence. Reliability was assessed using intraclass correlations (ICC) estimated with random coefficient models. Results: Overall, the 27 items had moderate-to-substantial reliability (ICC = 0.41-0.74). Few statistically significant differences were found in ICC between the education groups or neighborhoods, although the ICCs were significantly larger among the low SES for items that measured perceptions of neighborhood greenery, interesting things to see, litter, traffic volume and speed, crime, and rowdy youth on the streets. Conclusion: For the majority of the items, poor reliability and subsequent exposure misclassification is no more or less likely among low educated respondents and residents of disadvantaged neighborhoods. Estimates of the association between neighborhood perceptions and physical activity therefore are likely to be similarly precise irrespective of the respondent's socioeconomic background. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP), and usual transport mode. Methods This investigation included 11 036 residents from 200 neighbourhoods in Brisbane, Australia. Respondents self-reported their usual transport mode (car or motorbike, public transport, walking or cycling). Indicators for individual-level SEP were education, occupation and household income; and neighbourhood disadvantage was measured using a census-derived index. Data were analysed using multilevel multinomia logistic regression. High SEP respondents and residents of the most advantaged neighbourhoods who used a private motor vehicle as their usual form of transport was the reference category. Results Compared with driving a motor vehicle, the odds of using public transport were higher for white collar employees (OR 1.68, 95% CrI 1.41-2.01), members of lower income households (OR 1.71 95% CrI 1.25-2.30) and residents of more disadvantaged neighbourhoods (OR 1.93, 95% CrI 1.46-2.54); and lower for respondents with a certificate-level education (OR 0.60, 95% CrI 0.49-0.74) and blue collar workers (OR 0.63, 95% CrI 0.50-0.81). The odds of walking for transport were higher for the least educated (OR 1.58, 95% CrI 1.18-2.11), those not in the labour force (OR 1.94,95% CrI 1.38-2.72), members of lower income households (OR 2.10, 95% CrI 1.23-3.64) and residents of more disadvantaged neighbourhoods (OR 2.73, 95% CrI 1.46-5.24). The odds of cycling were lower among less educated groups (OR 0.31, 95% CrI 0.19-0.48). Conclusions The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual-level and neighbourhood-level mechanisms behind choice of transport mode, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes. [ABSTRACT FROM AUTHOR]

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 significantly 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 may reflect their poorer health status and the impact of adverse socioeconomic exposures over the life course. Each of these declines represents a significant challenge to public health advocates, urban designers, and planners in their attempts to keep people active and healthy in their later years of life. [ABSTRACT FROM AUTHOR]

We developed a theoretical framework to organize obesity prevention interventions by their likely impact on the socioeconomic gradient of weight. The degree to which an intervention involves individual agency versus structural change influences socioeconomic inequalities in weight. Agentic interventions, such as stand alone social marketing, increase socioeconomic inequalities. Structural interventions, such as food procurement policies and restrictions on unhealthy foods in schools, show equal or greater benefit for lower socioeconomic groups. Many obesity prevention interventions belong to the agento– structural types of interventions, and account for the environment in which health behaviors occur, but they require a level of individual agency for behavioral change, including workplace design to encourage exercise and fiscal regulation of unhealthy foods or beverages. Obesity prevention interventions differ in their effectiveness across socioeconomic groups. Limiting further increases in socioeconomic inequalities in obesity requires implementation of structural interventions. Further empirical evaluation, especially of agento– structural type interventions, remains crucial. [ABSTRACT FROM AUTHOR]

Abstract: Residents of socioeconomically disadvantaged neighbourhoods are more likely to walk for transport than their counterparts in advantaged neighbourhoods; however, the reasons for higher rates of transport walking in poorer neighbourhoods remain unclear. We investigated this issue using data from the HABITAT study of physical activity among 11,037 mid-aged residents of 200 neighbourhoods in Brisbane, Australia. Using a five-step mediation analysis and multilevel regression, we found that higher levels of walking for transport in disadvantaged neighbourhoods was associated with living in a built environment more conducive to walking (i.e. greater street connectivity and land use mix) and residents of these neighbourhoods having more limited access to a motor vehicle. The health benefits that accrue to residents of disadvantaged neighbourhoods as a result of their higher levels of walking for transport might help offset the negative effects of less healthy behaviours (e.g. smoking, poor diet), thus serving to contain or reduce neighbourhood inequalities in chronic disease. [Copyright &y& Elsevier]

Background Reducing disparities in cancer outcomes is a major priority for cancer-control agencies. The authors examine the relationships between geographic remoteness, area disadvantage and risk of advanced breast cancer among women. Methods Multilevel models were used to assess the area and individual-level contributions to the risk of advanced breast cancer among women aged 30-79 years diagnosed as having breast cancer in Queensland, Australia between 1997 and 2006 (n=18 658). Results Women who resided in the most socioeconomically disadvantaged areas were significantly more likely (OR 1.21, 95% CI 1.07 to 1.37) than residents of the most advantaged areas to be diagnosed as having advanced breast cancer after adjustment for individual-level factors. When geographic remoteness and area-disadvantage (and all the individual-level factors) were simultaneously adjusted, the rates of advanced breast cancer were significantly higher for women residing in Outer Regional areas (OR 1.13, 95% CI 1.02 to 1.24) and those who lived in the most disadvantaged areas (OR 1.16, 95% CI 1.02 to 1.32). There was no statistically significant interaction between geographic remoteness and area disadvantage. Conclusions A woman's risk of being diagnosed as having advanced breast cancer depends on where she lives, separate from the individual characteristics of the woman herself. Both the rurality and socio-economic characteristics of the geographical area in which women lived were important. The socio-economic factors contributing to advanced breast cancer, existing in both urban and rural environments, need to be investigated. [ABSTRACT FROM AUTHOR]

ABSTRACT Aims To assess the association between access to off-premises alcohol outlets and harmful alcohol consumption. Design, setting and participants Multi-level study of 2334 adults aged 18-75 years from 49 census collector districts (the smallest spatial unit in Australia at the time of survey) in metropolitan Melbourne. Measurements Alcohol outlet density was defined as the number of outlets within a 1-km road network of respondents' homes and proximity was the shortest road network distance to the closest outlet from their home. Using multi-level logistic regression we estimated the association between outlet density and proximity and four measures of harmful alcohol consumption: drinking at levels associated with short-term harm at least weekly and monthly; drinking at levels associated with long-term harm and frequency of consumption. Findings Density of alcohol outlets was associated with increased risk of drinking alcohol at levels associated with harm. The strongest association was for short-term harm at least weekly [odds ratio (OR) 1.10, 95% confidence interval (CI) 1.04-1.16]. When density was fitted as a categorical variable, the highest risk of drinking at levels associated with short-term harm was when there were eight or more outlets (short-term harm weekly: OR 2.36, 95% CI 1.22-4.54 and short-term harm monthly: OR 1.80, 95% CI 1.07-3.04). We found no evidence to support an association between proximity and harmful alcohol consumption. Conclusions The number of off-premises alcohol outlets in a locality is associated with the level of harmful alcohol consumption in that area. Reducing the number of off-premises alcohol outlets could reduce levels of harmful alcohol consumption. [ABSTRACT FROM AUTHOR]

Purpose: To examine the association between neighborhood disadvantage and physical activity (PA). Methods: We use data from the HABITAT multilevel longitudinal study of PA among middle-aged (40–65 years) men and women (N = 11,037, 68.5% response rate) living in 200 neighborhoods in Brisbane, Australia. PA was measured using three questions from the Active Australia Survey (general walking, moderate, and vigorous activity), one indicator of total activity, and two questions about walking and cycling for transport. The PA measures were operationalized by using multiple categories based on time and estimated energy expenditure that were interpretable with reference to the latest PA recommendations. The association between neighborhood disadvantage and PA was examined with the use of multilevel multinomial logistic regression and Markov chain Monte Carlo simulation. The contribution of neighborhood disadvantage to between-neighborhood variation in PA was assessed using the 80% interval odds ratio. Results: After adjustment for sex, age, living arrangement, education, occupation, and household income, reported participation in all measures and levels of PA varied significantly across Brisbane''s neighborhoods, and neighborhood disadvantage accounted for some of this variation. Residents of advantaged neighborhoods reported significantly higher levels of total activity, general walking, moderate, and vigorous activity; however, they were less likely to walk for transport. There was no statistically significant association between neighborhood disadvantage and cycling for transport. In terms of total PA, residents of advantaged neighborhoods were more likely to exceed PA recommendations. Conclusions: Neighborhoods may exert a contextual effect on the likelihood of residents participating in PA. The greater propensity of residents in advantaged neighborhoods to do high levels of total PA may contribute to lower rates of cardiovascular disease and obesity in these areas. [Copyright &y& Elsevier]

Abstract: This study examined relationships between individual-level socioeconomic position, area-level disadvantage, characteristics of the takeaway food environment, and the purchase of takeaway food. ‘Takeaway’ is conceptualised as foods or meals that are prepared and purchased outside of the home, and ready for immediate consumption either at the place of purchase or elsewhere. The analytic sample comprised 1001 households and 50 small areas in Brisbane, Australia. Takeaway food was purchased more regularly by high-income householders and those with higher levels of education. Residents of advantaged areas purchased takeaway food more regularly, although area differences attenuated to the null after adjustment for individual-level compositional factors. Number of takeaway shops in the local food environment, and road distance to the closest takeaway shop, were largely unrelated to the purchase of takeaway food. We conclude that there is little evidence that takeaway food purchasing in Brisbane is influenced by area-level socioeconomic disadvantage or features of the takeaway food environment. Rather, it seems that what matters most in terms of influencing the decision or capacity of Brisbane residents to purchase takeaway food are the socioeconomic characteristics of individuals and their households. The findings of this and previous analyses of the Brisbane Food Study data suggest that policy and health promotion aimed at improving the diets of residents and reducing dietary inequalities between socioeconomic groups should focus on people more so than places. [Copyright &y& Elsevier]

Objectives: To examine the association between neighborhood disadvantage and individual-level socioeconomic position (SEP) and self-reported oral health. Methods: A population-based cross-sectional study conducted in 2003 among males and females aged 43–57 years. The sample comprised 2915 individuals and 60 neighborhoods and was selected using a stratified two-stage cluster design. Data were collected using a mail survey (69.4% response rate). Neighborhood disadvantage was measured using a census-based composite index, and individual-level SEP was measured using education and household income. Oral health was indicated by self-reports of the impact of oral conditions on quality of life (0 = none or minor, 1 = severe), self-rated oral health (0 = excellent–good, 1 = fair/poor) and missing teeth (measured as a quantitative outcome). Data were analyzed using multilevel modeling. Results: After adjusting for age, sex, education, and household income, residents of socioeconomically disadvantaged neighborhoods were significantly more likely than those in more advantaged neighborhoods to indicate negative impacts of oral conditions on quality of life, to assess their oral health as fair or poor, and to report greater tooth loss. In addition, respondents with low levels of education and those from a low income household reported poorer oral health for each outcome independent of neighborhood disadvantage. Conclusions: The socioeconomic characteristics of neighborhoods are important for oral health over and above the socioeconomic characteristics of the people living in those neighborhoods. Policies and interventions to improve population oral health should be directed at the social, physical and infrastructural characteristics of places as well as individuals (i.e. the traditional target of intervention efforts). [ABSTRACT FROM AUTHOR]

Objectives: To examine whether area level socioeconomic disadvantage and social capital have different relations with women's and men's self rated health. Methods: The study used data from 15 112 respondents to the 1998 Tasmanian (Australia) healthy communities study (60% response rate) nested within 41 statistical local areas. Gender stratified analyses were conducted of the associations between the index of relative socioeconomic disadvantage (IRSD) and social capital (neighbourhood integration, neighbourhood alienation, neighbourhood safety, political participation, social trust, trust in institutions) and individual level self rated health using multilevel logistic regression analysis before (age only) and after adjustment for individual level confounders (marital status, indigenous status, income, education, occupation, smoking). The study also tested for interactions between gender and area level variables. Results: IRSD was associated with poor self rated health for women (age adjusted p<0.00) and men (age adjusted p<0.00), however, the estimates attenuated when adjusted for individual level variables. Political participation and neighbourhood safety were protective for women's self rated health but not for men's. Interactions between gender and political participation (p = 0.010) and neighbourhood safety (p=0.023) were significant. Conclusions: These finding suggest that women may benefit more than men from higher levels of area social capital. [ABSTRACT FROM AUTHOR]

Links between low socioeconomic position and poor health are well established. Most previous research, however, has focused on middle-aged males and has relied on limited socioeconomic data, usually measured at one point over the life course. This paper examines all-cause, cardiovascular, and noncardiovascular mortality in women in relation to socioeconomic position at different stages of the life course. Information was collected in 1965, 1974, 1983, and 1994 and included recalled father’s occupation and education as a measure of childhood socioeconomic position and the respondent’s household income, education and occupation, and spouse’s occupation from a sample of 3,087 women participating in the Alameda County Study. Cox regression models were used to estimate hazard ratios for risk of death. Lower childhood socioeconomic position was associated with an increased mortality due to cardiovascular disease (hazard ratio (HR) = 1.29, 95% confidence interval (CI): 1.09, 1.54) but was unrelated to death due to other causes (HR = 0.97, 95% CI: 0.82, 1.15). Overall mortality was higher among women reporting the lowest level of education (HR = 1.17, 95% CI: 0.99, 1.39), but education was most strongly related to noncardiovascular disease-related deaths (HR = 1.41, 95% CI: 1.10, 1.81). Low household income was also associated with higher mortality, for both cardiovascular disease-related (HR = 1.47, 95% CI: 1.14, 1.91) and noncardiovascular disease-related (HR = 1.30, 95% CI: 1.03, 1.63) deaths. Both early and later life indicators of socioeconomic position contribute to increased mortality risk among socioeconomically disadvantaged women, but these effects appear stronger for cardiovascular mortality. [ABSTRACT FROM AUTHOR]

Background While the relationship between socio-economic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. The authors examined the association between education attainment and CVD mortality and the extent to which behavioural, social and physiological factors explained this relationship. Methods Adults (n=38⇔355) aged 40-69 years living in Melbourne, Australia were recruited in 1990-1994. Subjects with baseline CVD risk factor data ascertained through questionnaire and physical measurement were followed for an average of 9.4 years with CVD deaths verified by review of medical records and autopsy reports. Results CVD mortality was higher for those with primary education only, compared with those who had completed tertiary education, with an HR of 1.66 (95% CI 1.10 to 2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared with the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78 to 1.77). In analysis of individual risk factors, smoking and waist circumference explained most of the difference in CVD mortality between the highest and lowest education groups. Conclusions Most of the excess CVD mortality in lower socio-economic groups can be explained by known risk factors, particularly smoking and overweight. While targeting cardiovascular risk factors should not divert efforts from addressing the underlying determinants of health inequalities, it is essential that known risk factors are addressed effectively among lower socio-economic groups. [ABSTRACT FROM AUTHOR]

Purpose: This study examines associations between neighborhood socioeconomic disadvantage and self-reported type 2 diabetes and heart disease, occurring separately and concurrently at a single time point (comorbidity).Methods: This study included 11,035 residents from 200 neighborhoods in Brisbane, Australia. Respondents self-reported type 2 diabetes and heart disease as long-term health conditions. Neighborhood socioeconomic disadvantage was measured using a census-derived composite index. Individual socioeconomic position was measured using education, occupation, and household income. Data were analyzed using multilevel multinomial mixed-effects logistic regression using Markov chain Monte Carlo simulation.Results: Compared with the most advantaged neighborhoods, residents of the most-disadvantaged neighborhoods were more likely to report type 2 diabetes (odds ratio [OR] = 2.21, 95% credible interval [CrI] = 1.55-3.15), heart disease (OR = 1.72, 95% CrI = 1.25-2.38), and comorbidity (OR = 4.38, 95% CrI = 2.27-8.66). This relationship attenuated after adjustment for individual-level socioeconomic position, but remained statistically significant for type 2 diabetes (OR = 1.81, 95% CrI = 1.15-2.83) and comorbidity (OR = 3.00, 95% CrI = 1.49-6.13).Conclusions: Studies of neighborhood disadvantage that fail to include individual-level socioeconomic measures may inflate associations. Establishing why residents of disadvantaged neighborhoods are more likely to experience the co-occurrence of heart disease and type 2 diabetes independent of their individual socioeconomic position warrants further investigation. [ABSTRACT FROM AUTHOR]

Abstract: Lower fruit and vegetable (F/V) intake among socioeconomically disadvantaged groups has been well documented, and may be a consequence of a higher consumption of take-out foods. This study examined whether, and to what extent, take-out food consumption mediated (explained) the association between socioeconomic position and F/V intake. A cross-sectional postal survey was conducted among 1,500 randomly selected adults aged 25 to 64 years in Brisbane, Australia, during 2009 (response rate 63.7%, N=903). A food frequency questionnaire assessed usual daily servings of F/V (0 to 6), overall take-out consumption (times per week), and the consumption of 22 specific take-out items (never to once per day or more). These specific take-out items were grouped into “less healthy” and “healthy” choices and indexes were created for each type of choice (0 to 100). Socioeconomic position was ascertained by education. The analyses were performed using linear regression, and a bootstrap resampling approach estimated the statistical significance of the mediated effects. Mean daily servings of F/V were 1.89±1.05 and 2.47±1.12, respectively. The least educated group members were more likely to consume fewer servings of fruit (β= −.39, P<0.001) and vegetables (β= −.43, P<0.001) compared with members of the highest educated group. The consumption of “less healthy” take-out food partly explained (mediated) education differences in F/V intake; however, no mediating effects were observed for overall and “healthy” take-out consumption. Regular consumption of “less healthy” take-out items may contribute to socioeconomic differences in F/V intake, possibly by displacing these foods. [Copyright &y& Elsevier]

Limitations have arisen when measuring associations between the neighbourhood social environment and physical activity, including same-source bias, and the reliability of aggregated neighbourhood-level social environment measures. This study examines cross-sectional associations between the neighbourhood social environment (perceptions of incivilities, crime, and social cohesion) and self-reported physical activity, while accounting for same-source bias and reliability of neighbourhood-level exposure measures, using data from a large population-based clustered sample. This investigation included 11,035 residents aged 40-65years from 200 neighbourhoods in Brisbane, Australia, in 2007. Respondents self-reported their physical activity and perceptions of the social environment (neighbourhood incivilities, crime and safety, and social cohesion). Models were adjusted for individual-level education, occupation, and household income, and neighbourhood disadvantage. Exposure measures were generated via split clusters and an empirical Bayes estimation procedure. Data were analysed in 2016 using multilevel multinomial logistic regression. Residents of neighbourhoods with the highest incivilities and crime, and lowest social cohesion were reference categories. Individuals were more likely to be in the higher physical activity categories if they were in neighbourhoods with the lowest incivilities and the lowest crime. No associations were found between social cohesion and physical activity. This study provides a basis from which to gain a clearer understanding of the relationship between the neighbourhood social environment and individual physical activity. Further work is required to explore the pathways between perceptions of the neighbourhood social environment and physical activity. [ABSTRACT FROM AUTHOR]