School health policies and practices in Victoria- a comparison involving socio-economic status

Issue addressed: Health programs have been part of the responsibility of Victorian school education for 90 years. Yet rarely have there been studies to identify what is happening in school health promotion, or what the differences between schools might be, particularly in relation to the socioeconomic status of the school community and whether the school is in a metropolitan or regional area. Methods: In 1997 all Victorian schools (primary and secondary) in the State, Catholic and Independent systems were sent questionnaires in order to promote broader awareness about health promotion, and to identify what health programs, policies and activities the schools believed existed within their school community. A response rate of 43% was achieved, and results were collated under the six domains of the Health Promoting School model as outlined by the Western Pacific Regional Office of the World Health Organisation. Data analysed in this paper compared highest versus lowest quartiles for socioeconomic status (SES), and schools in metropolitan Melbourne versus regional areas. Results: Most differences between schools based on socioeconomic status occurred in secondary schools and were related mainly to environmental policies and practices, use of back packs, the presence of safety policies, involvement of parents in school activities and the provision of services for mental and social health needs. All differences were in favour of the highest SES quartile schools. Environmental policies and procedures, and school-based health and welfare services were present more often in metropolitan schools than in regional and rural schools. Conclusion: Although there were notable differences between schools, the audit results pointed to more similarities than differences between schools in the highest and lowest SES quartiles for health-related policies and practices; there were even fewer differences between metropolitan and non-metropolitan schools. So what: Regardless of the actual advantages and disadvantages schools experience with respect to location or socioeconomic status, it is important to understand that school staff perceive that they can and do have reasonably comprehensive health policies, procedures and practices to address health issues. Nevertheless, clear differences between schools did emerge in certain health areas and findings will assist policy making and the allocation of limited resources.

Understanding the role of mediating risk factors and proxy effects in the association between socio-economic status and untreated hypertension

The association between socio-economic status (SES) and untreated hypertension varies according to a country's level of development and racial/ethnic group. We sought to confirm this variation in women from China and the United States (US) as well as to investigate the impact of SES on several mediating risk factors. We also investigate the extent to which SES explains racial/ethnic differences in untreated hypertension in the US. We used cross-sectional data from 1814 non-pregnant women in China (China Health and Nutrition Survey (CHNS), 1997) and 3266 non-pregnant women in the United States (National Health and Nutrition Examination Survey (NHANES III), 1988–1994) respectively. A variety of statistical modelling techniques was used to predict untreated hypertension as a function of several mediating factors and to simulate the impact of changes in SES. The age-adjusted prevalence of untreated hypertension was significantly higher (p<0.01) for low-income White and Black women compared to Mexican American or Chinese women. Untreated hypertension was not significantly associated with income or education in Mexican Americans or women in China. Obesity and light physical activity had the largest mediating effect on the association between SES and untreated hypertension for all racial/ethnic groups. However, this effect was not as strong as the proxy effect of income and education. SES did not completely explain racial/ethnic differences in hypertension in the US. While SES was more strongly associated with hypertension in Blacks than Whites, Blacks were still 1.97 (95% CI 1.47–2.64) times more likely to have untreated hypertension than Whites after adjusting for SES differences. The association between SES and untreated hypertension varied by country and racial/ethnic group. An important explanation for this variation was the differential effect of SES on mediating risk factors. SES disparities between Whites and Blacks in the US partly explain differences in the prevalence of untreated hypertension between these racial/ethnic groups.

Trends in children`s physical activity and weight status in high and low socio-economic status areas of Melbourne, Victoria, 1985-2001

Objective:
To examine trends in active transport to and from school, in school sport and physical education (PE), and in weight status among children from high and low socio-economic status (SES) areas in Melbourne, Victoria, between 1985 and 2001.

Methods:
Cross-sectional survey data and measured height and weight from 1985 (n=557) and 2001 (n=926) were compared for children aged between 9–13 years within high and low SES areas.

Results:
From 1985 to 2001, the frequency of walking to or from school declined (4.38±4.3 vs. 3.61 ± 3.8 trips/wk, p<0.001), cycling to or from school also declined (1.22±2.9 vs. 0.36±1.5 trips/wk, p<0.001), and the frequency of PE lessons declined (1.64±1.1 vs. 1.18±0.9 lessons/wk, p<0.001). However, the frequency of school sport increased (0.9±1.22 vs. 1.24±0.8 sessions/wk, p<0.001). In 1985, 11.7% of children were overweight or obese compared with 28.7% in 2001 (p<0.001). Apart from walking to school and school sport, there were greater relative declines in cycling to school and PE, and increases in overweight and obesity among children attending schools in low SES areas compared with those attending schools in high SES areas.

Conclusions:
Declines in active school transport and PE have occurred at the same time as increases in overweight and obesity among Australian children.

Implications:
Promoting active school transport and maintaining school sport and PE should be important public health priorities in Australia. Current inequities in school sport and PE and in prevalence of overweight and obesity by area-level SES also need to be addressed.

Investigating socio-economic status and chronic illness: directions and dilemmas

In Australia, chronic illness is increasing being recognised as more important. Yet there is relatively little discussion of the nature of the role played by socio-economic status (SES) plays in its prevalence. This paper argues there are two effects of SES. The first is that lower SES can lead to an increase in chronic illness, as evidenced by a number of epidemiological studies. The second is that chronic illness can contribute to lower SES. Examples are provided of the different types of relationships. Difficulties associated with SES analyses and its relationship to chronic illness are discussed, and specific conditions such as HIV/AIDS are referred to as examples. In addition the work of Marmot on SES and chronic illness is drawn on. The authors identify a number of areas that require further research, and recommend that in studies of chronic illness, SES may be a contributing variable, and outcome, or both.

The measurement of socio-economic status: investigation of gender-and age-specific indicators in Australia: national health survey 1995

Objective: To investigate thecorrelations between age- and gender-specificmeasures of socio-economic status versus healthstatus as measured by the SF-36.

Design: Population based study.

Participants: 38187 people aged between18 to 79 years who participated in the NationalHealth Survey in 1995.

Results: Factor analysis producedconsistent results that were interpreted interms of five conceptually meaningful domains(employment, housing, migration, family unitand education). The relative rank of thefactors differs between groups and in somecases factor composition requires items to beadded or deleted from the conceptual domains.

Conclusions: Age- and gender-specific SESscores based on these factors had strongerassociations with the physical and mentalcomponents of SF-36 than either an area basedindex or scores derived from males aged 40–44years. Overall the results supported thehypothesis that SES measures composed of socialand demographic items exhibit important age-and gender-specific differences which arerelevant for health.

Which aspects of socio-economic status are related to health in mid-aged and older women?

A population-based study was conducted to validate gender- and age-specific indexes of socio-economic status (SES) and to investigate the associations between these indexes and a range of health outcomes in 2 age cohorts of women. Data from 11,637 women aged 45 to 50 and 9,510 women aged 70 to 75 were analyzed. Confirmatory factor analysis produced four domains of SES among the mid-aged cohort (employment, family unit, education, and migration) and four domains among the older cohort (family unit, income, education, and migration). Overall, the results supported the factor structures derived from another population-based study (Australian Bureau of Statistics, 1995), reinforcing the argument that SES domains differ across age groups. In general, the findings also supported the hypotheses that women with low SES would have poorer health outcomes than higher SES women, and that the magnitude of these effects would differ according to the specific SES domain and by age group, with fewer and smaller differences observed among older women. The main exception was that in the older cohort, the education domain was significantly associated with specific health conditions. Results suggest that relations between SES and health are highly complex and vary by age, SES domain, and the health outcome under study.

Dietary patterns of Australian adults and their association with socio-economic status: results from the 1995 national nutrition survey

Objective: To describe dietary patterns among men and women in the Australian population, and to explore how these varied according to socioeconomic status (SES).

Design: A cross-sectional self-report population survey, the 1995 Australian National Nutrition Survey (NNS), was used.

Setting: Private dwelling sample, covering urban and rural areas across Australia.

Subjects: Data provided by 6680 adults aged 18-64 who participated in the NNS were used in the analyses.

Methods: Factor analyses were used to analyse data from a Food Frequency Questionnaire (FFQ) completed by participants. Associations between SES and dietary pattens were assessed using ANOVA.

Results: Separate factor analyses of the FFQ data for men and women revealed 15 factors, accounting for approximately 50% of the variance in both men's and women's dietary patterns. Several gender and SES differences in food patterns were observed. Lower SES males more frequently consumed 'tropical fruits', 'protein foods', and 'offal and canned fish', while high SES males more often ate 'breakfast cereals' and 'wholemeal bread'. Lower SES females more often ate 'traditional vegetables', 'meat dishes' and 'pasta, rice and other mixed foods', while high SES females more frequently ate 'ethnic vegetables' and 'breakfast cereal/muesli'.

Conclusions: These findings contribute to a better understanding of the dietary patterns that underscore gender-specific SES differences in nutrient intakes. Analyses of the type employed in this study will facilitate the development of interventions aimed at modifying overall eating patterns, rather than specific components of the diet.

Equity indicators: measures of socio-economic status at an Australian university

After reviewing relevant literature on socio-economic status (SES) and the ways in which it is used for higher education institutional research and policy, a detailed data analysis of Victoria University (Australia) student data was undertaken. Between 10,000 and 15,000 domestic student addresses were ‘geocoded’ to Australian Bureau of Statistics (ABS) collection district level. A survey of individual reenrolling 2001 students that included parental occupation and education data was also analysed. The most important findings were: (1) The debate for practical reasons tends to focus on area versus individual measures, but SES is a richer and more complex subject and must be acknowledged as such. (2) It is apparent that VU’s student catchment is on average of lower SES than the Melbourne average, using various area measures of SES, including the DEST-Martin indicators. (3) There is only a very small difference between average area SES measures at the collection district and the postcode level. In practical terms this means that the postcode method is adequate, as well as being cheaper and more efficiently obtained, for analyses at an aggregated (or average) level. (4) Individual surveys of students do not prima facie add to the quality of aggregated institution level SES results delivered by area analyses. This again suggests that the postcode method is best for practical reasons.

How socio-economic status contributes to participation in leisure-time physical activity

The aim of this cross-sectional study was to identify individual, social, and environmental contributors (mediators) to individual- and area-level differences in leisure-time physical activity across socio-economic groups. A two-stage stratified sampling design was used to recruit 20–65 year old adults (N = 2194) living in 154 census collection districts of Adelaide, Australia (overall response rate: 12%). Participants completed two surveys six months apart (response rate on the second survey: 83%). Individual-level socio-economic status (SES) was assessed using self-report measures on educational attainment, household income, and household size. Area-level SES was assessed using census data on median household income and household size for each selected census district. Bootstrap generalized linear models were used to examine associations between SES, potential mediators, and leisure-time physical activity. The product-of-coefficient test was used to estimate mediating effects. All SES measures were independently associated with potential individual and social mediators of the SES-activity relationships. Individual- and area-level income was also associated with perceived neighborhood attributes. Self-efficacy and social support for physical activity explained virtually all of the differences in physical activity across educational attainment groups. Physical barriers to walking and access to public open space contributed in part to the explanation of differences in recreational walking across income groups. Yet, self-efficacy and social support were the key mediators of the observed relationships between individual- and area-level income and physical activity. This study suggests that in order to increase physical activity participation in the more disadvantaged segments of the population, comprehensive, multilevel interventions targeting activity-related attitudes and skills as well as social and physical environments are needed.

Do features of public open spaces vary according to neighbourhood socio-economic status?

This study examined the relations between neighbourhood socio-economic status and features of public open spaces (POS) hypothesised to influence children's physical activity. Data were from the first follow-up of the Children Living in Active Neighbourhoods (CLAN) Study, which involved 540 families of 5–6 and 10–12-year-old children in Melbourne, Australia. The Socio-Economic Index for Areas Index (SEIFA) of Relative Socio-economic Advantage/Disadvantage was used to assign a socioeconomic index score to each child's neighbourhood, based on postcode. Participant addresses were geocoded using a Geographic Information System. The Open Space 2002 spatial data set was used to identify all POS within an 800 m radius of each participant's home. The features of each of these POS (1497) were audited. Variability of POS features was examined across quintiles of neighbourhood SEIFA. Compared with POS in lower socioeconomic neighbourhoods, POS in the highest socioeconomic neighbourhoods had more amenities (e.g. picnic tables and drink fountains) and were more likely to have trees that provided shade, a water feature (e.g. pond, creek), walking and cycling paths, lighting, signage regarding dog access and signage restricting other activities. There were no differences across neighbourhoods in the number of playgrounds or the number of recreation facilities (e.g. number of sports catered for on courts and ovals, the presence of other facilities such as athletics tracks, skateboarding facility and swimming pool). This study suggests that POS in high socioeconomic neighbourhoods possess more features that are likely to promote physical activity amongst children.