742 resultados para Economic Status


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From the moment children are born, they begin a lifetime journey of learning about themselves and their surroundings. With the establishment of the No Child Left Behind Act of 2001, it mandates that all children receive a high-quality education in a positive school climate. Regardless of the school the child attends or the neighborhood in which the child lives, proper and quality education and resources must be provided and made available in order for the child to be academically successful. The purpose of this ex post facto study was to investigate the relationship between the FCAT 2.0 mathematics scores of public middle school students in Miami-Dade County, Florida and the concentrations of a school's racial and ethnic make-up (Whites, Blacks, and Hispanics), English for Speakers of other Languages (ESOL) population, socio-economic status (SES), and school climate. The research question of this study was: Is there a significant relationship between the FCAT 2.0 Mathematics scores and racial and ethnic concentration of public middle school students in Miami-Dade County when controlling SES, ESOL student population, and school climate for the 2010-2011 school year? The instruments used to collect the data were the FCAT 2.0 and Miami-Dade County Public Schools (M-DCPS) School Climate Survey. The study found that Economically Disadvantaged (SES) students socio-economic status had the strongest correlation with the FCAT 2.0 mathematics scores (r = -.830). The next strongest correlation was with the number of students who agreed that their school climate was positive and helped them learn (r = .741) and the third strongest correlation was a school percentage of White students (r = .668). The study concluded that the FCAT 2.0 mathematics scores of M-DCPS middle school students have a significant relationship with socio-economic status, school climate, and racial concentration.

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Background: Parental obesity is a predominant risk factor for childhood obesity. Family factors including socio-economic status (SES) play a role in determining parent weight. It is essential to unpick how shared family factors impact on child weight. This study aims to investigate the association between measured parent weight status, familial socio-economic factors and the risk of childhood obesity at age 9. Methodology/Principal Findings: Cross sectional analysis of the first wave (2008) of the Growing Up in Ireland (GUI) study. GUI is a nationally representative study of 9-year-old children (N = 8,568). Schools were selected from the national total (response rate 82%) and age eligible children (response rate 57%) were invited to participate. Children and their parents had height and weight measurements taken using standard methods. Data were reweighted to account for the sampling design. Childhood overweight and obesity prevalence were calculated using International Obesity Taskforce definitions. Multinomial logistic regression examined the association between parent weight status, indicators of SES and child weight. Overall, 25% of children were either overweight (19.3%) or obese (6.6%). Parental obesity was a significant predictor of child obesity. Of children with normal weight parents, 14.4% were overweight or obese whereas 46.2% of children with obese parents were overweight or obese. Maternal education and household class were more consistently associated with a child being in a higher body mass index category than household income. Adjusted regression indicated that female gender, one parent family type, lower maternal education, lower household class and a heavier parent weight status significantly increased the odds of childhood obesity. Conclusions/Significance: Parental weight appears to be the most influential factor driving the childhood obesity epidemic in Ireland and is an independent predictor of child obesity across SES groups. Due to the high prevalence of obesity in parents and children, population based interventions are required.

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The globalization contributes to rapid economic developments and great changes of lifestyle in Madre de Dios of Peru, both of which have influenced the health status of local people in direct and indirect ways. The high overweight and obesity rate has become one of the biggest health challenges in this region. This study quantitatively analyzed the impact of household economic status and food consumption patterns on overweight and obesity, and tried to establish their relationship with local economic activities. People living in mining communities are more likely to be overweight or obese. Increased family incomes and lacks of health knowledge are two important reasons. The large consumption of soda and alcohol are positively associated with overweight and obesity. In addition, lack of physical activities is also one of the risk factors of overweight and obesity.

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Background

Kidscreen-27 was developed as part of a cross-cultural European Union-funded project to standardise the measurement of children’s health-related quality of life. Yet, research has reported mixed evidence for the hypothesised 5-factor model, and no confirmatory factor analysis (CFA) has been conducted on the instrument with children of low socio-economic status (SES) across Ireland (Northern and Republic).

Method

The data for this study were collected as part of a clustered randomised controlled trial. A total of 663 (347 male, 315 female) 8–9-year-old children (M = 8.74, SD = .50) of low SES took part. A 5- and modified 7-factor CFA models were specified using the maximum likelihood estimation. A nested Chi-square difference test was conducted to compare the fit of the models. Internal consistency and floor and ceiling effects were also examined.

Results

CFA found that the hypothesised 5-factor model was an unacceptable fit. However, the modified 7-factor model was supported. A nested Chi-square difference test confirmed that the fit of the 7-factor model was significantly better than that of the 5-factor model. Internal consistency was unacceptable for just one scale. Ceiling effects were present in all but one of the factors.

Conclusions

Future research should apply the 7-factor model with children of low socio-economic status. Such efforts would help monitor the health status of the population.

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Skeletal maturity is used to evaluate biological maturity status. Information about the association between socio-economic status (SES) and skeletal maturity is limited in Portugal. Aims: The aim of this study is to document the skeletal maturity of youths in Madeira and to evaluate variation in maturity associated with SES. Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed-longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Skeletal age was estimated from radiographs of the hand and wrist using the Tanner–Whitehouse 2 method (TW2). Social class rankings were based on Graffar’s (1956) method. Five social rankings were subsequently grouped into three SES categories: high, average and low. Results: Median for the radius, ulna and short finger bones (RUS scores) in the total sample of boys and girls increased curvilinearly across age whereas median for the 7 (without pisiform) carpal bones (Carpal scores) increased almost linearly. The 20-bone maturity scores demonstrated distinctive trends by gender: the medians for boys increased almost linearly while the medians for girls increased curvilinearly. SES differences were minimal. Only among children aged 10–11 years were high SES boys and girls advanced in skeletal maturity. Madeira adolescents were advanced in skeletal maturity compared with Belgian reference values. Conclusion: The data suggests population variation in TW2 estimates of skeletal maturation. Skeletal maturity was not related to SES in youths from Madeira.

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Within a country social conditions change over time and these conditions vary from country to country. The associations between these conditions, somatic growth, physical activity and fitness reflect these changes. Aim: The study documented variation in somatic growth, physical activity and fitness associated with socio-economic status (SES). Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Anthropometric measurements included lengths, body mass, skeletal breadths, girths and skinfolds. Physical activity and SES were collected via questionnaire and interview. Physical fitness was assessed using the Eurofit test battery. Variation in somatic growth, physical activity and physical fitness by SES (high, average and low) was tested with analysis of variance. Results: Significant differences between SES groups were observed for height, body mass and skinfolds. Boys and girls from high SES groups were taller, heavier and fatter (subscapular and triceps skinfolds) than their peers from average and low SES groups. At some age intervals, the high SES group had larger skeletal breadths (girls) and girths (boys and girls) than low SES. Small SES differences were observed for physical activity (sport and leisure-time indices). SES was significantly associated with physical fitness. At some age levels, boys from the low SES group performed better for muscular and aerobic endurance whereas girls from the high SES group performed better for power. Conclusion: Considerable variation in somatic growth and physical fitness in association with SES has been demonstrated, but little association was found for physical activity.

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Skeletal maturity is used to evaluate biological maturity status. Information about the association between socio-economic status (SES) and skeletal maturity is limited in Portugal. Aims: The aim of this study is to document the skeletal maturity of youths in Madeira and to evaluate variation in maturity associated with SES. Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed-longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Skeletal age was estimated from radiographs of the hand and wrist using the Tanner–Whitehouse 2 method (TW2). Social class rankings were based on Graffar’s (1956) method. Five social rankings were subsequently grouped into three SES categories: high, average and low. Results: Median for the radius, ulna and short finger bones (RUS scores) in the total sample of boys and girls increased curvilinearly across age whereas median for the 7 (without pisiform) carpal bones (Carpal scores) increased almost linearly. The 20-bone maturity scores demonstrated distinctive trends by gender: the medians for boys increased almost linearly while the medians for girls increased curvilinearly. SES differences were minimal. Only among children aged 10–11 years were high SES boys and girls advanced in skeletal maturity. Madeira adolescents were advanced in skeletal maturity compared with Belgian reference values. Conclusion: The data suggests population variation in TW2 estimates of skeletal maturation. Skeletal maturity was not related to SES in youths from Madeira.

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Within a country social conditions change over time and these conditions vary from country to country. The associations between these conditions, somatic growth, physical activity and fitness reflect these changes. Aim: The study documented variation in somatic growth, physical activity and fitness associated with socio-economic status (SES). Subjects and methods: The study involved 507 subjects (256 boys and 251 girls) from the Madeira Growth Study, a mixed longitudinal study of five cohorts (8, 10, 12, 14 and 16 years of age) followed at yearly intervals over 3 years (1996–1998). A total of 1493 observations were made. Anthropometric measurements included lengths, body mass, skeletal breadths, girths and skinfolds. Physical activity and SES were collected via questionnaire and interview. Physical fitness was assessed using the Eurofit test battery. Variation in somatic growth, physical activity and physical fitness by SES (high, average and low) was tested with analysis of variance. Results: Significant differences between SES groups were observed for height, body mass and skinfolds. Boys and girls from high SES groups were taller, heavier and fatter (subscapular and triceps skinfolds) than their peers from average and low SES groups. At some age intervals, the high SES group had larger skeletal breadths (girls) and girths (boys and girls) than low SES. Small SES differences were observed for physical activity (sport and leisure-time indices). SES was significantly associated with physical fitness. At some age levels, boys from the low SES group performed better for muscular and aerobic endurance whereas girls from the high SES group performed better for power. Conclusion: Considerable variation in somatic growth and physical fitness in association with SES has been demonstrated, but little association was found for physical activity.

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This research investigates relationships between parental socio economic status and daughters' career aspirations; linking family background and the career choices made by teenage girls. Drawing on Bourdieu's theory of cultural capital, and figures produced by the Bradley Report's investigation, two Queensland State High Schools are the investigative platform to address the research questions. A quantitative data analysis investigated if a correlation between the indicators existed. The significance of the findings will contribute to future decision making regarding educational practices and socio economic backgrounds and to support the Bradley Report target of 20% of low SES students accessing higher education. The outcomes found that female students' aspirations are influenced by parental background in a variety of significant ways. An understanding of these assists schools in understanding how to influence girls' future aspirations.

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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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A number of factors have been shown to influence residential property prices in various locations. Studies have identified the importance of location in relation to services, transport and proximity to negative factors such as power lines and cell phone towers. Often the socio-economic status of a residential precinct can determine the overall quality and nature of the streetscapes in that area, with higher value suburbs or locations offering a better visual appearance compared to areas where these factors are not present. However, does the same value for a good streetscape apply in lower socio-economic areas or a buyers more motivated by less aesthetic factors such as size of the house, construction materials or land size. This paper analyses specific streets in a lower to middle socio-economic suburb of Christchurch New Zealand to determine if the location of a house in a street with good streetscape appeal has greater value, investment performance and saleability compared to adjoining streets with less aesthetic appeal.

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Although the relationship between socioeconomic status (SES) and health is well documented for developed countries, less evidence has been presented for developing countries. The aim of this paper is to analyse this relationship at the household level for Fiji, a developing country in the South Pacific, using original household survey data. To allow for the endogeneity of SES status in the household health production function, we utilize a simultaneous equation approach where estimates are achieved by full information maximum likelihood. By restricting our sample to one, relatively small island, and including area and district hospital effects, physical geography effects are unpacked from income effects. We measure SES, as permanent income which is constructed using principal components analysis. An alternative specification considers transitory household income. We find that a 1% increase in wealth (our measure of permanent income) would lead to a 15% decrease in the probability of an incapacitating illness occurring intra-household. Although the presence of a strong relationship indicates that relatively small improvements in SES status can significantly improve health at the household level, it is argued that the design of appropriate policy would also require an understanding of the various mechanisms through which the relationship operates.

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Aim Worldwide obesity levels have increased unprecedentedly over the past couple of decades. Although the prevalence, trends and associated socio-economic factors of the condition have been extensively reported in Western populations, less is known regarding South Asian populations. Methods A review of articles using Medline with combinations of the MeSH terms: 'Obesity', 'Overweight' and 'Abdominal Obesity' limiting to epidemiology and South Asian countries. Results Despite methodological heterogeneity and variation according to country, area of residence and gender , the most recent nationally representative and large regional data demonstrates that without any doubt there is a epidemic of obesity, overweight and abdominal obesity in South Asian countries. Prevalence estimates of overweight and obesity (based on Asian cut-offs: overweight ≥ 23 kg/m(2), obesity ≥ 25 kg/m(2)) ranged from 3.5% in rural Bangladesh to over 65% in the Maldives. Abdominal obesity was more prevalent than general obesity in both sexes in this ethnic group. Countries with the lowest prevalence had the highest upward trend of obesity. Socio-economic factors associated with greater obesity in the region included female gender, middle age, urban residence, higher educational and economic status. Conclusion South Asia is significantly affected by the obesity epidemic. Collaborative public health interventions to reverse these trends need to be mindful of many socio-economic constraints in order to provide long-term solutions.

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Social marketers and governments have often targeted hard to reach or vulnerable groups (Gordon et al., 2006) such as young adults and low income earners. Past research has shown that low-income earners are often at risk of poor health outcomes and diminished lifestyle (Hampson et al., 2009; Scott et al., 2012). Young adults (aged 18 to 35) are in a transition phase of their life where lifestyle preferences are still being formed and are thus a useful target for long-term sustainable change. An area of focus for all levels of government is the use of energy with an aim to reduce consumption. There is little research to date that combines both of these groups and in particular in the context of household energy usage. Research into financially disadvantaged consumers is challenging the notion that that low income consumer purchasing and usage of products and services is based upon economic status (Sharma et al., 2012). Prior research shows higher income earners view items such as televisions and computers as necessities rather than non-essential (Karlsson et al., 2004). Consistent with this is growing evidence that low income earners purchase non-essential, energy intensive electronic appliances such as multiple big screen TV sets and additional refrigerators. With this in mind, there is a need for knowledge about how psychological and economic factors influence the energy consumption habits (e.g. appliances on standby power, leaving appliances turned on, running multiple devices at one time) of low income earners. Thus, our study sought to address the research question of: What are the factors that influence young adult low-income earners energy habits?