8 resultados para Social Class

em University of Queensland eSpace - Australia


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Objective Comparisons of the changing patterns of inequalities in occupational mortality provide one way to monitor the achievement of equity goals. However, previous comparisons have not corrected for numerator/denominator bias, which is a consequence of the different ways in which occupational details are recorded on death certificates and on census forms. The objective of this study was to measure the impact of this bias on mortality rates and ratios over time. Methods Using data provided by the Australian Bureau of Statistics, we examined the evidence for bias over the period 1981-2002, and used imputation methods to adjust for this bias. We compared unadjusted with imputed rates of mortality for manual/non-manual workers. Findings Unadjusted data indicate increasing inequality in the age-adjusted rates of mortality for manual/non-manual workers during 1981-2002, Imputed data suggest that there have been modest fluctuations in the ratios of mortality for manual/non-manual workers during this time, but with evidence that inequalities have increased only in recent years and are now at historic highs. Conclusion We found that imputation for missing data leads to changes in estimates of inequalities related to social class in mortality for some years but not for others. Occupational class comparisons should be imputed or otherwise adjusted for missing data on census or death certificates.

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Background There are substantial social inequalities in adult male mortality in many countries. Smoking is often more prevalent among men of lower social class, education, or income. The contribution of smoking to these social inequalities in mortality remains uncertain. Methods The contribution of smoking to adult mortality in a population can be estimated indirectly from disease-specific death rates in that population (using absolute lung cancer rates to indicate proportions due to smoking of mortality from certain other diseases). We applied these methods to 1996 death rates at ages 35-69 years in men in three different social strata in four countries, based on a total of 0.6 million deaths. The highest and lowest social strata were based on social class (professional vs unskilled manual) in England and Wales, neighbourhood income (top vs bottom quintile) in urban Canada, and completed years of education (more than vs less than 12 years) in the USA and Poland. Results In each country, there was about a two-fold difference between the highest and the lowest social strata in overall risks of dying among men aged 35-69 years (England and Wales 21% vs 43%, USA 20% vs 37%, Canada 21% vs 34%, Poland 26% vs 50%: four-country mean 22% vs 41%, four-country mean absolute difference 19%). More than half of this difference in mortality between the top and bottom social strata involved differences in risks of being killed at age 35-69 years by smoking (England and Wales 4% vs 19%, USA 4% vs 15%, Canada 6% vs 13%, Poland 5% vs 22%: four-country mean 5% vs 17%, four-country mean absolute difference 12%). Smoking-attributed mortality accounted for nearly half of total male mortality in the lowest social stratum of each country. Conclusion In these populations, most, but not all, of the substantial social inequalities in adult male mortality during the 1990s were due to the effects of smoking. Widespread cessation of smoking could eventually halve the absolute differences between these social strata in the risk of premature death.

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Background. Although smoking cessation programs significantly reduce smoking rates in the general population, some sectors are poorly motivated by them, especially healthy men from lower socioeconomic classes. Methods. By using a significant life event (approaching birth of a child) we exploited a time of increased receptiveness to smoking cessation influences. A multicomponent intervention was conducted and evaluated using a stratified, randomised control trial, with an intention to treat analysis. Results. Five hundred and sixty-one men were enrolled and 505 (90%) followed to the end of their partners' pregnancy. At 6-month follow-up 16.5% of 291 smokers of the intervention group and 9.3% of 270 in the control group reported they had stopped smoking (P = 0.011, OR = 0.52, 95% CI 0.31 - 0.86). The strongest predictors of smoking cessation were being in a skilled occupation, having a higher number of quit attempts in the previous year and having the first cigarette of the day relatively later. Conclusions. The number of smoking men who had to be treated to achieve one stopping smoking (NNT) during their partner's pregnancy was 13 to 14. Innovative antismoking population health measures for the partners of antenatal patients are effective and perhaps should be more widely adopted. (C) 2003 American Health Foundation and Elsevier Inc. All rights reserved.

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This paper updates single risk factors identified by the Northern Finland 1966 Birth Cohort Study up to the end of year 2001 or age 34. Impaired performance (e.g., delayed motor or intellectual development) or adverse exposures (e.g., pregnancy and birth complications, central nervous system diseases) are associated with an increased risk for schizophrenia. However, upper social class girls and clever schoolboys also have an increased risk to develop schizophrenia, contrasted to their peers. Individuals who subsequently develop schizophrenia follow a developmental trajectory that partly and subtly differs from that of the general population; this trajectory lacks flexibility and responsiveness compared to control subjects, at least in the early stages. We propose a descriptive, lifespan, multilevel systems model on the development and course of schizophrenia.

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Background Evidence on the relative influence of childhood vs adulthood socioeconomic conditions on obesity risk is limited and equivocal. The objective of this study was to investigate associations of several indicators of mothers', fathers', and own socioeconomic status, and intergenerational social mobility, with body mass index (BMI) and weight change in young women. Methods This population-based cohort study used survey data provided by 8756 women in the young cohort (aged 18-23 years at baseline) of the Australian Longitudinal Study on Women's Health. In 1996 and 2000, women completed mailed surveys in which they reported their height and weight, and their own, mother's, and father's education and occupation. Results Multiple linear regression models showed that both childhood and adulthood socioeconomic status were associated with women's BMI and weight change, generally in the hypothesized (inverse) direction, but the associations varied according to socioeconomic status and weight indicator. Social mobility was associated with BMI (based on father's socioeconomic status) and weight change (based on mother's socioeconomic status), but results were slightly less consistent. Conclusions Results suggest lasting effects of childhood socioeconomic status on young women's weight status, independent of adult socioeconomic status, although the effect may be attenuated among those who are upwardly socially mobile. While the mechanisms underlying these associations require further investigation, public health strategies aimed at preventing obesity may need to target families of low socioeconomic status early in children's lives.

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This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a 'self-medicating' subgroup is needed.