Gavin Turrell

Measuring socio-economic position in dietary research: is choice of socio-economic indicator important?

OBJECTIVES To examine the association between socio-economic position (SEP) and diet, by assessing the unadjusted and simultaneously adjusted (independent) contributions of education, occupation and household income to food purchasing behaviour. DESIGN The sample was randomly selected using a stratified two-stage cluster design, and the response rate was 66.4%. Data were collected by face-to-face interview. Food purchasing was examined on the basis of three composite indices that reflected a households choice of grocery items (including meat and chicken), fruit and vegetables. SETTING Brisbane City, Australia, 2000. PARTICIPANTS : Non-institutionalised residents of private dwellings located in 50 small areas (Census Collectors Districts). RESULTS When shopping, respondents in lower socio-economic groups were less likely to purchase grocery foods that were high in fibre and low in fat, salt and sugar. Disadvantaged groups purchased fewer types of fresh fruits and vegetables, and less often, than their counterparts from more advantaged backgrounds. When the relationship between SEP and food purchasing was examined using each indicator separately, education and household income made an unadjusted contribution to purchasing behaviour for all three food indices; however, occupation was significantly related only with the purchase of grocery foods. When education and occupation were simultaneously adjusted for each other, the socio-economic patterning with food purchase remained largely unchanged, although the strength of the associations was attenuated. When household income was introduced into the analysis, the association between education, occupation and food purchasing behaviour was diminished or became non-significant; income, however, showed a strong, graded association with food choice. CONCLUSIONS The food purchasing behaviours of socio-economically disadvantaged groups were least in accord with dietary guideline recommendations, and hence are more consistent with greater risk for the development of diet-related disease. The use of separate indicators for education, occupation and household income each adds something unique to our understanding of how socio-economic position is related to diet: each indicator reflects a different underlying social process and hence they are not interchangeable, and do not serve as adequate proxies for one another.

Urban area disadvantage and physical activity: a multilevel study in Melbourne, Australia

Objective: To estimate variation between small areas in the levels of walking, cycling, jogging, and swimming and overall physical activity and the importance of area level socioeconomic disadvantage in predicting physical activity participation. Methods: All census collector districts (CCDs) in the 20 innermost local government areas in metropolitan Melbourne, Australia, were identified and ranked by the percentage of low income households (<

City planning and population health: a global challenge

400/week) living in the CCD. Fifty CCDs were randomly selected from the least, middle, and most disadvantaged septiles of the ranked CCDs and 2349 residents (58.7% participation rate) participated in a cross sectional postal survey about physical activity. Multilevel logistic regression (adjusted for extrabinomial variation) was used to estimate area level variation in walking, cycling, jogging, and swimming and in overall physical activity participation, and the importance of area level socioeconomic disadvantage in predicting physical activity participation. Results: There were significant variations between CCDs in all activities and in overall physical participation in age and sex adjusted models; however, after adjustment for individual SES (income, occupation, education) and area level socioeconomic disadvantage, significant differences remained only for walking (p = 0.004), cycling (p = 0.003), and swimming (p = 0.024). Living in the most socioeconomically disadvantaged areas was associated with a decreased likelihood of jogging and of having overall physical activity levels that were sufficiently active for health; these effects remained after adjustment for individual socioeconomic status (sufficiently active: OR 0.70, 95% CI 0.55 to 0.90 and jogging: OR = 0.69, 95% CI 0.51 to 0.94). Conclusion: These research findings support the need to focus on improving local environments to increase physical activity participation.

Weight and place: a multilevel cross-sectional survey of area-level social disadvantage and overweight/obesity in Australia

Significant global health challenges are being confronted in the 21st century, prompting calls to rethink approaches to disease prevention. A key part of the solution is city planning that reduces non-communicable diseases and road trauma while also managing rapid urbanisation. This Series of papers considers the health impacts of city planning through transport mode choices. In this, the first paper, we identify eight integrated regional and local interventions that, when combined, encourage walking, cycling, and public transport use, while reducing private motor vehicle use. These interventions are destination accessibility, equitable distribution of employment across cities, managing demand by reducing the availability and increasing the cost of parking, designing pedestrian-friendly and cycling-friendly movement networks, achieving optimum levels of residential density, reducing distance to public transport, and enhancing the desirability of active travel modes (eg, creating safe attractive neighbourhoods and safe, affordable, and convenient public transport). Together, these interventions will create healthier and more sustainable compact cities that reduce the environmental, social, and behavioural risk factors that affect lifestyle choices, levels of traffic, environmental pollution, noise, and crime. The health sector, including health ministers, must lead in advocating for integrated multisector city planning that prioritises health, sustainability, and liveability outcomes, particularly in rapidly changing low-income and middle-income countries. We recommend establishing a set of indicators to benchmark and monitor progress towards achievement of more compact cities that promote health and reduce health inequities.

Does gender modify associations between self rated health and the social and economic characteristics of local environments

Objective:To estimate variation between small areas in adult body mass index (BMI), and assess the importance of area level socioeconomic disadvantage in predicting BMI.Methods:We identified all census collector districts (CCDs) in the 20 innermost Local Government Areas in metropolitan Melbourne, Australia, and ranked them by the percentage of low income households (<

Sedentary behaviour and health: mapping environmental and social contexts to underpin chronic disease prevention

400/week). In all, 50 CCDs were randomly selected from the least, middle and most disadvantaged septiles of the ranked list and 4913 residents (61.4% participation rate) completed one of two surveys. Multilevel linear regression was used to estimate area level variance in BMI and the importance of area level socioeconomic disadvantage in predicting BMI.Results:There were significant variations in BMI between CCDs for women, even after adjustment for individual and area SES (P=0.012); significant area variation was not found for men. Living in the most versus least disadvantaged areas was associated with an average difference in BMI of 1.08 kg/m2 (95% CI: 0.48–1.68 kg/m2) for women, and of 0.93 kg/m2 (95% CI: 0.32–1.55 kg/m2) for men. Living in the mid versus least disadvantaged areas were associated with an average difference in BMI of 0.67 kg/m2 (95% CI: 0.09–1.26 kg/m2) for women, and 0.43 kg/m2 for men (95% CI: −0.16–1.01).Conclusion:These findings suggest that area disadvantage is an important predictor of adult BMI, and support the need to focus on improving local environments to reduce socioeconomic inequalities in overweight and obesity.

Food insecurity among adults residing in disadvantaged urban areas: potential health and dietary consequences

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<0.001) and men (age adjusted p<0.001), 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.

Smokers living in deprived areas are less likely to quit: A longitudinal follow-up

The time that children and adults spend sedentary–put simply, doing too much sitting as distinct from doing too little physical activity—has recently been proposed as a population-wide, ubiquitous influence on health outcomes. It has been argued that sedentary time is likely to be additional to the risks associated with insufficient moderate-to-vigorous physical activity. New evidence identifies relationships of too much sitting with overweight and obesity, type 2 diabetes, cardiovascular disease, some cancers and other adverse health outcomes. There is a need for a broader base of evidence on the likely health benefits of changing the relevant sedentary behaviours, particularly gathering evidence on underlying mechanisms and dose–response relationships. However, as remains the case for physical activity, there is a research agenda to be pursued in order to identify the potentially modifiable environmental and social determinants of sedentary behaviour. Such evidence is required so as to understand what might need to be changed in order to influence sedentary behaviours and to work towards population-wide impacts on prolonged sitting time. In this context, the research agenda needs to focus particularly on what can inform broad, evidence-based environmental and policy initiatives. We consider what has been learned from research on relationships of environmental and social attributes and physical activity; provide an overview of recent-emerging evidence on relationships of environmental attributes with sedentary behaviour; argue for the importance of conducting international comparative studies and addressing life-stage issues and socioeconomic inequalities and we propose a conceptual model within which this research agenda may be addressed.

Neighborhood Disadvantage and Physical Activity: Baseline Results from the HABITAT Multilevel Longitudinal Study

OBJECTIVE Food insecurity is the limited or uncertain availability or access to nutritionally adequate, culturally appropriate and safe foods. Food insecurity may result in inadequate dietary intakes, overweight or obesity and the development of chronic disease. Internationally, few studies have focused on the range of potential health outcomes related to food insecurity among adults residing in disadvantaged locations and no such Australian studies exist. The objective of the present study was to investigate associations between food insecurity, sociodemographic and health factors and dietary intakes among adults residing in disadvantaged urban areas. DESIGN Data were collected by mail survey (n 505, 53 % response rate), which ascertained information about food security status, demographic characteristics (such as age, gender, household income, education) fruit and vegetable intakes, takeaway and meat consumption, general health, depression and chronic disease. SETTING Disadvantaged suburbs of Brisbane city, Australia, 2009. SUBJECTS Individuals aged ≥ 20 years. RESULTS Approximately one in four households (25 %) was food insecure. Food insecurity was associated with lower household income, poorer general health, increased health-care utilisation and depression. These associations remained after adjustment for age, gender and household income. CONCLUSIONS Food insecurity is prevalent in urbanised disadvantaged areas in developed countries such as Australia. Low-income households are at high risk of experiencing food insecurity. Food insecurity may result in significant health burdens among the population, and this may be concentrated in socio-economically disadvantaged suburbs.

The socio-economic patterning of survey participation and non-response error in a multilevel study of food purchasing behaviour: area- and individual-level characteristics

Objective: To follow up smokers to examine whether the likelihood of quitting smoking varied by area deprivation, and whether smoking history, health status, personality characteristics, social support and stressful situations contributed to differences in area deprivation in quit rates. Design: Longitudinal data with a 6-year follow-up period were analysed using multilevel logistic regression. Area-level deprivation was characterised by a composite measure that was the sum of the proportion of unemployed residents, the percentage of residents in blue-collar occupations and the proportion with only elementary-level education. Previously established predictors of smoking cessation, including education, age at smoking initiation, self-assessed health, chronic illness, locus of control, neuroticism, negative life events, longlasting relationship difficulties, emotional social support and negative neighbourhood conditions were examined separately and in a combined model to assess whether they contributed to neighbourhood deprivation differences in quitting. Participants: 404 participants (residing in 83 areas) identified as smokers at baseline and who did not change their residential address over the follow-up period. Main outcome: Being a non-smoker at follow-up. Results: Odds ratios of quitting decreased with greater area-level deprivation, but differences reached significance only between the most and least deprived quartiles. Smoking history, health status, personality characteristics, social support and stressful situations did not contribute to the lower quitting rates seen among smokers in deprived areas. Conclusions: Living in a deprived area seems to reduce the likelihood of quitting smoking; hence individual-level tobacco control efforts should be complemented with area-based interventions. However, we need to identify and understand the underlying factors associated with living in a deprived area that contributes to lower quitting rates.