170 resultados para Socioeconomic inequalities


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Background : Although the association between lower socioeconomic status (SES) and obesity in women in developed countries is well-documented, current evidence regarding the relationship between obesity in men and area-based SES (equivalised for advantage and disadvantage) is inconsistent. Therefore, we aimed to examine obesity, lifestyle behaviours, physical activity in different domains and demographics in men using area-based SES.

Methods :
We performed a descriptive cross-sectional study of 1467 randomly selected white men (mean age 56 year (inter-quartile range (IQR) = 39–73 year)) recruited from the Barwon Statistical Division, South Western Victoria, Australia between 2001–06.

Results :
Age-adjusted BMI, waist circumference, % fat and lean mass and blood pressure were inversely associated with SES, with differences between low and upper SES (P for difference <0.05), independent of country of birth. Age-adjusted lifestyle behaviours associated with obesity and/or adverse health (especially cardiovascular disease), were also associated with lower SES.

Conclusions :
Subjects from lower SES had greater measures of obesity despite being more physically active at work, but were less likely to be physically active in the domains of sports and/or leisure. These findings suggest the possible influence of lifestyle behaviours and occupation upon obesity in men and should be investigated further.

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Overall, socioeconomic status (SES) is inversely associated with poorer health outcomes. However, current literature provides conflicting data of the relationship between SES and bone mineral density (BMD) in men. In an age-stratified population-based randomly selected cross-sectional study of men (n = 1467) we assessed the association between SES and lifestyle exposures in relation to BMD. SES was determined by matching the residential address for each subject with Australian Bureau of Statistics 2006 census data for the study region. BMD was measured at the spine and femoral neck by dual energy X-ray absorptiometry. Lifestyle variables were collected by self-report. Regression models were age-stratified into younger and older groups and adjusted for age, weight, dietary calcium, physical activity, and medications known to affect bone. Subjects with spinal abnormalities were excluded from analyses of BMD at the spine. In younger men, BMD was highest at the spine in the mid quintiles of SES, where differences were observed compared to quintile 1 (1–7%, p < 0.05). In older men, the pattern of BMD across SES quintiles was reversed, and subjects from mid quintiles had the lowest BMD, with differences observed compared to quintile 5 (1–7%, p < 0.05). Differences in BMD at the spine across SES quintiles represent a potential 1.5-fold increase in fracture risk for those with the lowest BMD. There were no differences in BMD at the femoral neck. Further research is warranted which examines the mechanisms that may underpin differences in BMD across SES quintiles and to address the current paucity of data in this field of enquiry.

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With few exceptions, an inverse relationship exists between social disadvantage and disease. However, there are conflicting data for the relationship between socioeconomic status (SES) and BMD. The aim of this study was to assess the association between SES and lifestyle exposures in relation to BMD. In a cross-sectional study conducted using 1494 randomly selected population-based adult women, we assessed the association between SES and lifestyle exposures in relation to BMD. BMD was measured at multiple anatomical sites by DXA. SES was determined by cross-referencing residential addresses with Australian Bureau of Statistics 1996 census data for the study region and categorized in quintiles. Lifestyle variables were collected by self-report. Regression models used to assess the relationship between SES and BMD were adjusted for age, height, weight, dietary calcium, smoking, alcohol consumption, physical activity, hormone therapy, and calcium/vitamin D supplements. Unadjusted BMD differed across SES quintiles (p < 0.05). At each skeletal site and SES index, a consistent peak in adjusted BMD was observed in the mid-quintiles. Differences in adjusted BMD were observed between SES quintiles 1 and 4 (3-7%) and between quintiles 5 and 4 (2-7%). At the spine, the maximum difference was observed (7.5%). In a subset of women, serum 25(OH)D explained a proportion of the association between SES and BMD (difference remained up to 4.2%). Observed differences in BMD across SES quintiles, consistent across both SES indices, suggest that low BMD may be evident for both the most disadvantaged and most advantaged.

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Summary : Although socioeconomic status (SES) is inversely related to most diseases, this systematic review showed a paucity of good quality data examining influences of SES on osteoporotic fracture to confirm this relationship. Further research is required to elucidate the issue and any underlying mechanisms as a necessary precursor to considering intervention implications.

Introduction :
The association between socioeconomic status (SES) and musculoskeletal disease is little understood, despite there being an inverse relationship between SES and most causes of morbidity. We evaluated evidence of SES as a risk factor for osteoporotic fracture in population-based adults.

Methods : Computer-aided search of Medline, EMBASE, CINAHL, and PsychINFO from January 1966 until November 2007 was conducted. Identified studies investigated the relationship between SES parameters of income, education, occupation, type of residence and marital status, and occurrence of osteoporotic fracture. A best-evidence synthesis was used to summarize the results.

Results :
Eleven studies were identified for inclusion, which suggested a lack of literature in the field. Best evidence analysis identified strong evidence for an association between being married/living with someone and reduced risk of osteoporotic fracture. Limited evidence exists of the relationship between occupation type or employment status and fracture, or for type of residence and fracture. Conflicting evidence exists for the relationship between osteoporotic fracture and level of income and education.

Conclusion :
Limited good quality evidence exists of the role SES might play in osteoporotic fracture. Further research is required to identify whether a relationship exists, and to elucidate underlying mechanisms, as a necessary precursor to considering intervention implications.

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This qualitative study compares experiences of men from low socioeconomic status (SES) communities who achieved sufficient physical activity (PA) with those who did not. The socioecological model of health guided interviews with men (n=25) and community health workers (n=4) to explore individual, interpersonal, organizational, community, environmental and policy influences on PA participation. Men generally reported that they had poor health, financial barriers, were unfamiliar with community PA facilities and programs, had limited social support, and lived in unsafe neighbourhoods. There were clear differences between active and inactive men. Inactive men described their inability to cope with poor health, and consequent perceptions of disconnection. They did not identify positive PA outcomes and seemed consumed by stressful life situations. Active men identified barriers to existing programs such as the exclusive culture of PA facilities. It is important that personal circumstances are understood, and financial and cultural barriers addressed to promote PA among men from low SES communities.

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This book is essential reading for Australasian mathematics educators and other researchers with an interest in the history of mathematics curriculum, the culture of mathematics, gender, and social justice issues in mathematics. Drawing on the results of research conducted by the Educational Outcomes Research Unit at the University of Melbourne and historical documents, Richard Teese argues that the education system fails to diffuse the economic and cultural benefits assumed to flow from the completion of secondary schooling.

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Aim and method: A comparison study of four six-year-old children attending a school with a play-based curriculum and a school with a traditionally structured classroom from low socioeconomic areas was conducted in Victoria, Australia. Children’s play,
language and social skills were measured in February and again in August. At baseline assessment there was a combined sample of 31 children (mean age 5.5 years, SD 0.35 years; 13 females and 18 males). At follow-up there was a combined sample of 26
children (mean age 5.9 years, SD 0.35 years; 10 females, 16 males).
Results: There was no significant difference between the school groups in play, language, social skills, age and sex at baseline assessment. Compared to norms on a standardised assessment, all the children were beginning school with delayed play ability. At follow-up assessment, children at the play-based curriculum school had made significant gains in all areas assessed (p values ranged from 0.000 to 0.05). Children at the school with the traditional structured classroom had made significant positive gains in use of symbols in play (p < 0.05) and semantic language (p < 0.05). At follow-up, there were significant differences between schools in elaborate play (p < 0.000), semantic language (p < 0.000), narrative language (p < 0.01) and social connection (p < 0.01), with children in the play-based curriculum school having significantly higher scores in play, narrative language and language and lower scores in social disconnection.
Implications: Children from low SES areas begin school at risk of failure as skills in play, language and social skills are delayed. The school experience increases children’s skills, with children in the play-based curriculum showing significant improvements in all areas assessed. It is argued that a play-based curriculum meets children’s developmental and learning needs more effectively. More research is needed to replicate these results.

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Introduction

Socio-economically disadvantaged women are at a greater risk of spending excess time engaged in television viewing, a behavior linked to several adverse health outcomes. However, the factors which explain socio-economic differences in television viewing are unknown. This study aimed to investigate the contribution of intrapersonal, social and environmental factors to mediating socio-economic (educational) inequalities in women's television viewing.
Methods

Cross-sectional data were provided by 1,554 women (aged 18-65) who participated in the 'Socio-economic Status and Activity in Women study' of 2004. Based on an ecological framework, women self-reported their socio-economic position (highest education level), television viewing, as well as a number of potential intrapersonal (enjoyment of television viewing, preference for leisure-time sedentary behavior, depression, stress, weight status), social (social participation, interpersonal trust, social cohesion, social support for physical activity from friends and from family) and physical activity environmental factors (safety, aesthetics, distance to places of interest, and distance to physical activity facilities).
Results

Multiple mediating analyses showed that two intrapersonal factors (enjoyment of television viewing and weight status) and two social factors (social cohesion and social support from friends for physical activity) partly explained the educational inequalities in women's television viewing. No physical activity environmental factors mediated educational variations in television viewing.
Conclusions

Acknowledging the cross-sectional nature of this study, these findings suggest that health promotion interventions aimed at reducing educational inequalities in television viewing should focus on intrapersonal and social strategies, particularly providing enjoyable alternatives to television viewing, weight-loss/management information, increasing social cohesion in the neighborhood and promoting friend support for activity.

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Aim:  This study compared the diets of breastfeeding and non-breastfeeding mothers from socioeconomically diverse regions of Melbourne to determine whether breastfeeding is a marker for healthier maternal dietary intakes.

Methods:
  This cross-sectional study obtained information via self-reported questionnaire from 529 first-time Melbourne mothers. Breastfeeding status was determined when the children were 3.9 months. Diet information was obtained using a validated Food Frequency Questionnaire. Maternal diet was assessed by seven indicators: average daily intake of fruit, vegetables, non-core drinks, non-core sweet snacks, non-core savoury snacks, variety of fruit and variety of vegetables eaten in the preceding 12 months. Associations between breastfeeding status and each dietary variable were assessed using linear regression analyses. Socioeconomic position, maternal body mass index and the cluster-based sampling design were controlled for.

Results:
  Of the 529 subjects, 70% were breastfeeding their child. Compared with non-breastfeeding mothers, breastfeeding mothers were found to consume more serves of vegetables (P= 0.001), a greater variety of fruit and vegetables (P= 0.001 and P≤ 0.001 respectively), and sweet snacks were consumed more frequently (P= 0.006). Differences were observed between low and high socioeconomic position mothers for fruit serves (P= 0.003), vegetable serves (P= 0.010) and fruit variety (P= 0.006). These associations persisted after controlling for socioeconomic position and maternal body mass index.

Conclusions: 
The association between infant feeding (breastfeeding) and some aspects of maternal diet provides further evidence suggesting a link between maternal and child diets from a younger age than previously examined.

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Background

Evidence for age-related variation in the relationship between obesity-related behaviours and socioeconomic position may assist in the targeting of dietary and physical activity interventions among children.
Objective

To investigate the relationship between different indicators of socioeconomic position and obesity-related behaviours across childhood and adolescence.
Methods

Data were from 4487 children aged 2 to 16 years participating in the cross-sectional 2007 Australian National Children's Nutrition and Physical Activity Survey. Socioeconomic position was defined by the highest education of the primary or secondary carer and parental income. Activity was assessed using recall methods with physical activity also assessed using pedometers. Intake of energy-dense drinks and snack foods, fruits and vegetables was assessed using 2 × 24-h dietary recalls.
Results

A socioeconomic gradient was evident for each dietary measure (although in age-specific analyses, not for energy-dense snacks in older children), as well as television viewing, but not physical activity. Whether each behaviour was most strongly related to parental income or education of the primary or secondary carer was age and sex dependent. The socioeconomic gradient was strongest for television viewing time and consumption of fruit and energy-dense drinks.
Conclusions

A strong socioeconomic gradient in eating behaviours and television viewing time was observed. Relationships for particular behaviours differed by age, sex and how socioeconomic position was defined. Socioeconomic indicators define different population groups and represent different components of socioeconomic position. These findings may provide insights into who should be targeted in preventive health efforts at different life stages.

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Objective: To describe how New South Wales (NSW) Area Health Service Chief Executive Officers (CEOs) understood concepts of equity in the development of NSW Health's Equity Statement; CEO knowledge and interpretation of a given concept being one aspect of developing policy.

Design and Setting: This paper describes the process through which NSW Area Health Service CEOs were involved in developing the Equity Statement, specifically:

1. Briefings with individual CEOs on key issues and identification of possible difficulties and potential 'equity champions'.
2. A two-hour workshop to explore ('pre-mortem') why the proposed statement might fail.
3. CEO involvement in identifying strategies that promoted equity already operating locally.
4. C onsultations with selected individuals about the draft recommendations.
5. Feedback to CEOs.

The article provides a case study of consultative policy making by illustrating how participant knowledge can both inform and be strengthened by involvement in the policy development process.

Results: There was a high level of awareness among CEOs of health inequalities and an acceptance of their responsibility to address them. They saw three main ways of doing this: a) equity of resource allocation for health service delivery within and between regions; b) equity of access to health services based on need; and c) equity of health outcomes. CEOs felt that making the health system accountable for health outcomes would provide pressure for system-wide resource allocation changes. They recognised that factors substantially impacting on health outcomes were outside the control of the health system. Furthermore, finding a balance to which they could be held accountable was difficult. All CEOs saw ensuring needs-based access to services as a key area where they could potentially have an impact; and they specifically saw challenges in a conflict between equity and efficiency, marginalisation of special treatment for disadvantaged people, balancing investment in rescue services and prevention/early intervention, and developing a rational health financing system. The resulting policy has been broadly embedded within the NSW health system with strong local support.

Conclusion: The NSW Health and Equity policy was embedded because CEO leadership and acceptance of the policy enhanced local ownership.

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The key discussions about the relationship between health and equity have understandably concerned the causal relationship between various social, economic, cultural and environmental determinants of health and the health status of populations by socioeconomic status, class or other divisions that may be used to illustrate health inequalities. (Acheson (1998); "Bringing Britain together" (1998); Kawachi et al (1997); Canada (1997); Dixon (1999); Marmot (1998); Wilkinson (1996); RACP (1999); WHO (1998), Cochrane/Campbell (2000))

Similarly, there has been key discussion about the nature of organizations and their ability to affect and/or respond to change. We know quite a deal about organizations and their structures. And we now have (as we be shown below) an understanding from both practice and theory of the changes needed for organizations to evolve successfully.