655 resultados para School inequalities

em Queensland University of Technology - ePrints Archive


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Strengthening cooperation between schools and parents is critical to improving learning outcomes for children. The chapter focuses on parental engagement in their children’s education in the early years of school. It considers issues of social and cultural capital as important to whether, or not, parents are involved in their children’s schooling. Analyses of data from a national representative sample of children and their families who participate in Growing up in Australia: The Longitudinal Study of Australian Children are presented. Results indicated that higher family socio-economic position was associated with higher levels of parental involvement and higher expectations about children’s future level of education.

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Introduction and Aims: Since the 1990s illicit drug use death rates in Australia have increased markedly. There is a notable gap in knowledge about changing socio-economic inequalities in drug use death rates. Some limited Australian and overseas data point to higher rates of drug death in the lowest socio-economic groups, but the paucity of available studies and their sometimes conflicting findings need to be addressed. Design and Methods: This paper uses data obtained from the Australian Bureau of Statistics (ABS) to examine changes in age-standardised drug-induced mortality rates for Australian males over the period 1981 – 2002. Socio-economic status was categorised as manual or non-manual work status. Results: With the rapid increase in drug-induced mortality rates in the 1990s, there was a parallel increase in socio-economic inequalities in drug-induced deaths. The decline in drug death rates from 2000 onwards was associated with a decline in socio-economic inequalities. By 2002, manual workers had drug death rates well over twice the rate of non-manual workers. Discussion: Three factors are identified which contribute to these socio-economic inequalities in mortality. First, there has been an age shift in deaths evident only for manual workers. Secondly, there has been an increase in availability until 1999 and a relative decline in the cost of the drug, which most often leads to drug death (heroin). Thirdly, there has been a shift to amphetamine use which may lead to significant levels of morbidity, but few deaths. [Najman JM, Toloo G, Williams GM. Increasing socio-economic inequalities in drug-induced deaths in Australia: 1981–2002.

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Background Takeaway consumption has been increasing and may contribute to socioeconomic inequalities in overweight/obesity and chronic disease. This study examined socioeconomic differences in takeaway consumption patterns, and their contributions to dietary intake inequalities. Method Cross-sectional dietary intake data from adults aged between 25 and 64 years from the Australian National Nutrition Survey (n= 7319, 61% response rate). Twenty-four hour dietary recalls ascertained intakes of takeaway food, nutrients and fruit and vegetables. Education was used as socioeconomic indicator. Data were analysed using logistic regression and general linear models. Results Thirty-two percent (n = 2327) consumed takeaway foods in the 24 hour period. Lower-educated participants were less likely than their higher-educated counterparts to have consumed total takeaway foods (OR 0.64; 95% CI 0.52, 0.80). Of those consuming takeaway foods, the lowest-educated group was more likely to have consumed “less healthy” takeaway choices (OR 2.55; 95% CI 1.73, 3.77), and less likely to have consumed “healthy” choices (OR 0.52; 95% CI 0.36, 0.75). Takeaway foods made a greater contribution to energy, total fat, saturated fat, and fibre intakes among lower than higher-educated groups. Lower likelihood of fruit and vegetable intakes were observed among “less healthy” takeaway consumers, whereas a greater likelihood of their consumption was found among “healthy” takeaway consumers. Conclusions Total and the types of takeaway foods consumed may contribute to socioeconomic inequalities in intakes of energy, total and saturated fats. However, takeaway consumption is unlikely to be a factor contributing to the lower fruit and vegetable intakes among socioeconomically-disadvantaged groups.

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Background: While the relationship between socioeconomic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. We 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 to those who had completed tertiary education, with a hazard ratio (HR) of 1.66 (95% confidence interval [CI] 1.11-2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared to the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78-1.77). 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 socioeconomic 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 socioeconomic groups.

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Background: Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.---------- Methods/Design: A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry. Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants’ medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.---------- Conclusions: Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics. This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)

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Aim: To examine the amount of money spent on food by household income, and to ascertain whether food expenditure mediates the relationship between household income and the purchase of staple foods consistent with Australian dietary guideline recommendations. ----- ----- Methods: In face-to-face interviews (n = 1003, 66.4% response rate), households in Brisbane, Australia were asked about their purchasing choices for a range of staple foods, including grocery items, fruits and vegetables. For each participant, information was obtained about their total weekly household food expenditure, along with their sociodemographic and household characteristics. ----- ----- Results: Household income was significantly associated with food expenditure; participants residing in higher-income households spent more money on food per household member than those from lower-income households. Lower income households were less likely to make food purchasing choices of dietary staples that were consistent with recommendations. However, food expenditure did not attenuate the relationship between household income and the purchase of staple foods consistent with dietary guideline recommendations. ----- ----- Conclusions: The findings suggest that food expenditure may not contribute to income inequalities in purchasing staple foods consistent with dietary guideline recommendations: instead, other material or psychosocial factors not considered in the current study may be more important determinants of these inequalities. Further research should examine whether expenditure on non-staple items and takeaway foods is a larger contributor to socioeconomic inequalities in dietary behavior.

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This Review examined socioeconomic inequalities in intakes of dietary factors associated with weight gain, overweight/obesity among adults in Europe. Literature searches of studies published between 1990 and 2007 examining socioeconomic position (SEP) and the consumption of energy, fat, fibre, fruit, vegetables, energy-rich drinks and meal patterns were conducted. Forty-seven articles met the inclusion criteria. The direction of associations between SEP and energy intakes were inconsistent. Approximately half the associations examined between SEP and fat intakes showed higher total fat intakes among socioeconomically disadvantaged groups. There was some evidence that these groups consume a diet lower in fibre. The most consistent evidence of dietary inequalities was for fruit and vegetable consumption; lower socioeconomic groups were less likely to consume fruit and vegetables. Differences in energy, fat and fibre intakes (when found) were small-to-moderate in magnitude; however, differences were moderate-to-large for fruit and vegetable intakes. Socioeconomic inequalities in the consumption of energy-rich drinks and meal patterns were relatively under-studied compared with other dietary factors. There were no regional or gender differences in the direction and magnitude of the inequalities in the dietary factors examined. The findings suggest that dietary behaviours may contribute to socioeconomic inequalities in overweight/obesity in Europe. However, there is only consistent evidence that fruit and vegetables may make an important contribution to inequalities in weight status across European regions.

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Background Socioeconomically-disadvantaged adults in developed countries experience a higher prevalence of a number of chronic diseases, such as cardiovascular disease, type 2 diabetes, osteoarthritis and some forms of cancer. Overweight and obesity are major risk factors for these diseases. Lower socioeconomic groups have a greater prevalence of overweight and obesity and this may contribute to their higher morbidity and mortality. International studies suggest that socioeconomic groups may differ in their self-perceptions of weight status and their engagement in weightcontrol behaviours (WCBs). Research has shown that lower socioeconomic adults are more likely to underestimate their weight status, and are less likely to engage in WCBs. This may contribute (in part) to the marked inequalities in weight status observed at the population level. There are few, and somewhat limited, Australian studies that have examined the types of weight-control strategies people adopt, the barriers to their weight control, the determinants of their perceived weight status and WCBs. Furthermore, there are no known Australian studies that have examined socioeconomic differences in these factors to better understand the reasons for socioeconomic inequalities in weight status. Hence, the overall aim of this Thesis is to examine why socioeconomically-disadvantaged group experience a greater prevalence of overweight and obesity than their more-advantaged counterparts. Methods This Thesis used data from two sources. Men and women aged 45 to 60 years were examined from both data source. First, the longitudinal Australian Diabetes, Obesity and Lifestyle (AusDiab) Study were used to advance our knowledge and understanding of socioeconomic differences in weight change, perceived weight status and WCBs. A total of 2753 participants with measured weights at both baseline (1999-2000) and follow-up (2004-2005) were included in the analyses. Percent weight change over the five-year interval was calculated and perceived weight status, WCBs and highest attained education were collected at baseline. Second, the Candidate conducted a postal questionnaire from 1013 Brisbane residents (69.8 % response rate) to investigate the relationship between socioeconomic position, determinants of perceived weight status, WCBs, and barriers and reasons to weight control. A test-retest reliability study was conducted to determine the reliability of the new measures used in the questionnaire. Most new measures had substantial to almost perfect reliability when considering either kappa coefficient or crude agreement. Results The findings from the AusDiab Study (accepted for publication in the Australian and New Zealand Journal of Public Health) showed that low-educated men and women were more likely to be obese at baseline compared to their higheducated respondents (O.R. = 1.97, 95 % C.I. = 1.30-2.98 and O.R. = 1.52, 95 % C.I. = 1.03-2.25, respectively). Over the five year follow-up period (1999-2000 to 2004- 05) there were no socioeconomic differences in weight change among men, however socioeconomically-disadvantaged women had greater weight gains. Participants perceiving themselves as overweight gained less weight than those who saw themselves as underweight or normal weight. There was no relationship between engaging in WCBs and five-year weight change. The postal questionnaire data showed that socioeconomically-disadvantaged groups were less likely to engage in WCBs. If they did engage in weight control, they were less likely to adopt exercise strategies, including moderate and vigorous physical activities but were more likely to decrease their sitting time to control their weight. Socioeconomically-disadvantaged adults reported more barriers to weight control; such as perceiving weight loss as expensive, requiring a lot of cooking skills, not being a high priority and eating differently from other people in the household. These results have been accepted for publication in Public Health Nutrition. The third manuscript (under review in Social Science and Medicine) examined socioeconomic differences in determinants of perceived weight status and reasons for weight control. The results showed that lower socioeconomic adults were more likely to specify the following reasons for weight control: they considered themselves to be too heavy, for occupational requirements, on recommendation from their doctor, family members or friends. Conversely, high-income adults were more likely to report weight control to improve their physical condition or to look more attractive compared with those on lower-incomes. There were few socioeconomic differences in the determinants of perceived weight status. Conclusions Education inequalities in overweight/obesity among men and women may be due to mis-perceptions of weight status; overweight or obese individuals in loweducated groups may not perceive their weight as problematic and therefore may not pay attention to their energy-balance behaviours. Socioeconomic groups differ in WCBs, and their reasons and perceived barriers to weight control. Health promotion programs should encourage weight control among lower socioeconomic groups. More specifically, they should encourage the engagement of physical activity or exercise and dietary strategies among disadvantaged groups. Furthermore, such programs should address potential barriers for weight control that disadvantaged groups may encounter. For example, disadvantaged groups perceive that weight control is expensive, requires cooking skills, not a high priority and eating differently from other people in the household. Lastly, health promotion programs and policies aimed at reducing overweight and obesity should be tailored to the different reasons and motivations to weight control experienced by different socioeconomic groups. Weight-control interventions targeted at higher socioeconomic groups should use improving physical condition and attractiveness as motivational goals; while, utilising social support may be more effective for encouraging weight control among lower socioeconomic groups.

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This study examines the influence of cancer stage, distance to treatment facilities and area disadvantage on breast and colorectal cancer spatial survival inequalities. We also estimate the number of premature deaths after adjusting for cancer stage to quantify the impact of spatial survival inequalities. Population-based descriptive study of residents aged <90 years in Queensland, Australia diagnosed with primary invasive breast (25,202 females) or colorectal (14,690 males, 11,700 females) cancers during 1996-2007. Bayesian hierarchical models explored relative survival inequalities across 478 regions. Cancer stage and disadvantage explained the spatial inequalities in breast cancer survival, however spatial inequalities in colorectal cancer survival persisted after adjustment. Of the 6,019 colorectal cancer deaths within 5 years of diagnosis, 470 (8%) were associated with spatial inequalities in non-diagnostic factors, i.e. factors beyond cancer stage at diagnosis. For breast cancers, of 2,412 deaths, 170 (7%) were related to spatial inequalities in non-diagnostic factors. Quantifying premature deaths can increase incentive for action to reduce these spatial inequalities.

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Introduction: Food insecurity is a social determinant of health and is defined as limited ability to access sufficient amounts of nutritionally adequate or safe food for a healthy and active life. Food insecurity is associated with poor health status and the exacerbation of other health inequalities. This study examined whether an association existed between 1) socioeconomic position (SEP) and food insecurity and 2) food insecurity and weight status. Methods: Data from the 1995 National Nutrition Survey was analysed. A random sample of households (n = 13 858) were asked about dietary habits and food choices. Information about gender, age, BMI, waist circumference, household income and whether the household had run out of money to purchase food in the previous 12 months was obtained and analysed using chi-square and logistic regression. Results: Income was significantly associated with food insecurity; households with lower income were at higher risk of food insecurity. Lower income males were nine times more likely to experience food insecurity and lower income females were three times more likely to experience food insecurity than their higher income counterparts. Food insecurity was significantly associated with body mass index (BMI) among women but not men. Women experiencing food insecurity were at higher risk of overweight/obesity according to BMI and waist circumference measures. Conclusion: Evidence suggests that low income households are at higher risk of food insecurity and women who are food insecure are at higher risk of being overweight or obese. Food insecurity may mediate the association between SEP and BMI.

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Introduction and aims: Individual smokers from disadvantaged backgrounds are less likely to quit, which contributes to widening inequalities in smoking. Residents of disadvantaged neighbourhoods are more likely to smoke, and neighbourhood inequalities in smoking may also be widening because of neighbourhood differences in rates of cessation. This study examined the association between neighbourhood disadvantage and smoking cessation and its relationship with neighbourhood inequalities in smoking. Design and methods: A multilevel longitudinal study of mid-aged (40-67 years) residents (n=6915) of Brisbane, Australia, who lived in the same neighbourhoods (n=200) in 2007 and 2009. Neighbourhood inequalities in cessation and smoking were analysed using multilevel logistic regression and Markov chain Monte Carlo simulation. Results: After adjustment for individual-level socioeconomic factors, the probability of quitting smoking between 2007 and 2009 was lower for residents of disadvantaged neighbourhoods (9.0%-12.8%) than their counterparts in more advantaged neighbourhoods (20.7%-22.5%). These inequalities in cessation manifested in widening inequalities in smoking: in 2007 the between-neighbourhood variance in rates of smoking was 0.242 (p≤0.001) and in 2009 it was 0.260 (p≤0.001). In 2007, residents of the most disadvantaged neighbourhoods were 88% (OR 1.88, 95% CrI 1.41-2.49) more likely to smoke than residents in the least disadvantaged neighbourhoods: the corresponding difference in 2009 was 98% (OR 1.98 95% CrI 1.48-2.66). Conclusion: Fundamentally, social and economic inequalities at the neighbourhood and individual-levels cause smoking and cessation inequalities. Reducing these inequalities will require comprehensive, well-funded, and targeted tobacco control efforts and equity based policies that address the social and economic determinants of smoking.