Socioeconomic position and mass media campaigns to prevent chronic disease

This cross-sectional study of a 45 to 60 year old Brisbane population examined socioeconomic differences in campaign reach, understanding of health language, and effectiveness, of a recent mass media health promotion campaign. Lower socioeconomic groups were reached significantly less and understood significantly less of the health language than higher socioeconomic groups thus contributing to the widening of the health inequality gap.

Change in walking for transport : a longitudinal study of the influence of neighbourhood disadvantage and individual-level socioeconomic position in mid-aged adults

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 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.

Associations between individual socioeconomic position, neighbourhood disadvantage, and transport mode: Baseline results from the HABITAT multilevel study

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 multinomial 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 (OR1.68, 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). Conclusion 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- and neighbourhood-level mechanisms behind transport mode choice, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.

Tracking people in 3D using position, size and shape

This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.