73 resultados para High school students - socio-economic
Resumo:
Variation of suicide with socio-economic status (SES) in urban NSW (Australia) during 1985-1994, by sex and country or region of birth, was examined using Poisson regression analysis of vital statistics and population data (age greater than or similar to 15 yr). Quintiles of SES were defined by municipality of residence and comparisons of suicide by SES were adjusted for age and country (or region) of birth (COB), and examined by COB. Risk of suicide in females was 28% that of males for all adults and 21% for youth (age 15-24 yr). Suicide risk was lower in males from southern Europe, Middle East and Asia, and higher in northern and eastern European males, compared to the Australian-born. Risks for suicide increased significantly with decreasing SES in males, but not in females. The relationship of male suicide and SES was stronger when controlled for COB. For males, the relative risk of suicide, adjusted for age and COB, was 66% higher in the lowest SES quintile compared to the highest quintile, and 39% higher for youth (age 15-24 yr). For male suicide, the population attributable fraction for SES (less than the highest quintile) was 27%. Analysis of SES differentials in male suicide according to COB indicated a significant inverse suicide gradient in relation to SES for the Australian-born and those burn in New Zealand and the United Kingdom or fire. but not in non-English speaking COB groups, except for Asia. For Australian-born males, suicide risk was 71% higher in the lowest SES group (compared to the highest), adjusted for age. These findings indicate that SES plays an important role in male suicide rates among the Australian-born and migrants from English-speaking countries and Asia, and among youth; but not in female suicide, nor suicide in most non-English speaking migrant groups. Reduction in SES differentials through economic and social policies may reduce male suicide in lower SES groups and should be seen to be at least as important as individual level interventions. (C) 1998 Elsevier Science Ltd. All rights reserved.
Resumo:
Participation in regular physical activity reduces the risk of cardiovascular disease and all-cause mortality as well as providing numerous health benefits.' The steepest decline in physical activity occurs during adolescence (approximately 15 to 18 years of age) and young adulthood (20 to 25 years).(2) Australian population studies have found that levels of physical inactivity are twice as high for those 20 to 29 years old as they are for those under 20 years old.(3,4) As college students move through this period of changing roles within family and peer groups, they may be expected to have specific preferences and expected outcomes for physical activity participation that are different from those they had previously as high school students.(5) Studies of physical activity determinants suggest that while there are some similarities between males and females, there are differences in preferences for specific types of activity.(6) Calfas et al.(5) found that women reported body image factors (weight loss, dissatisfaction with body) to be more motivating, while young men rated strength (muscle gain, muscle tone) and social aspects (organized competition, meeting people) of physical activity more highly than did young women. We examined preferred physical activities, sources of assistance to be more active, and perceived motivators for activity in a sample of inactive college students. Differences between males and females were examined, and the implications for campus-based physical activity promotion strategies are considered.
Resumo:
Objective: This study examines the variation in coronary heart disease (CHD) mortality and acute myocardial infarction (AMI) by socio-economic status (SES), country of birth (COB) and geography (urban/rural) in the total population of New South Wales (Australia) in 1991-95. Method: CHD deaths and AMI are from complete enumerations of deaths and hospital admissions, respectively; and population denominators are from census information. Data are examined separately by sex, and comparisons of SES groups (based on municipalities), COB and region are analysed using Poisson regression, after adjustment for age. Results: The study identified higher risk for AMI admissions and CHD mortality in lower SES populations with significant linear trends, for both sexes, adjusted for age, region and COB. According to the population attributable fractions (PAF), 23-41% of the risk of CHD occurrence is due to SES lower than the highest quartile. The higher age-adjusted risk for CHD occurrence in rural and remote populations for both sexes, compared with urban communities, was lessened by adjustment for COB, and all but abolished when also adjusted for SES. COB analysis indicated significantly lower age-adjusted AMI admissions and CHD mortality compared with the Australian-born, Conclusions: Higher risks for CHD in rural populations compared with the capital city (Sydney) are due, in part, to lower SES, lesser migrant composition. Implications: Strategies for reducing CHD differentials should consider demographic factors and the fundamental need to reduce socio-economic inequalities, as well as targeting appropriate prevention measures.
Resumo:
Background The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. Methods All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic index for Australia) values from the ABS. Results Age-standardized all-cause mortality varies twofold from 5.7 to 11.3 per 1000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Conclusions Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.