Economic, social and cultural influences on the status and wellbeing of Indian rural wives

Examines the status and well being of wives in rural India using results from interviews. Surveys were conducted in three villages in the southwest of West Bengal and in three villages in the west of Orissa. The survey in West Bengal contained a large proportion of Santal tribals and the Oriyan survey was dominated by Kondh tribals. The relationships between variables representing economic, social and cultural factors are compared with ‘dependent’ variables representing the status of wives within their family and their wellbeing. Wellbeing is indicated by whether the basic needs of wives for food and medical care are met. Status of wives is indicated by their ‘control’ over family resources, whether or not they are restricted in joining social groups and in working outside their home, and the extent of their involvement in family decision-making. Cultural factors are found to be the dominant influence on the status of wives. Family income and other economic factors are found to be associated cross sectionally with greater restrictions on wives within their family. Nevertheless, the higher in the economic status of the household, the more likely are the basic needs of wives to be met.

Socio-economic, migrant and geographic differentials in coronary heart disease occurrence in New South Wales

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.

Variation in cervical cancer screening by region, socio-economic, migrant and Indigenous status in women in New South Wales

The purpose of this study was to estimate the extent of association of cervical screening in NSW women with socio-economic status (SES), rurality, and proportions of non-English speaking background (NESB) and Indigenous status. Data on women who had at least one Pap test over two years (January 1998-December 1999) were obtained from the NSW Pap test Register. Each local government area (LGA) was allocated to categories of population proportions of NESB and Indigenous status, a rurality classification based on population density and remoteness, and to an SES quintile. The odds ratios (OR) of having a Pap test were estimated and confounding adjusted by multiple logistic regression analysis. Implied Pap test rates in urban NESB and in rural Indigenous women were estimated from the modelled estimates. The adjusted OR for a Pap test in large rural centres (1.14) was significantly higher than those for metropolitan or capital city residents (0.9 and 1.0 respectively). Adjusted OR for a Pap test in other rural centres (0.73) and other remote areas (0.64) were significantly lower than those for metropolitan or capital city residents. In urban populations the lowest OR were in areas with both low SES and high proportion of NESB. The lowest OR for Pap screening in rural populations occurred in the most remote areas with the highest proportion of Indigenous women. For urban NESB women the biennial Pap test rate was estimated as 50%, and for rural Indigenous women 29%, compared with the NSW average of 59%.

Epidemiological modelling (including economic modelling) and its role in preventive drug therapy

In contrast to curative therapies, preventive therapies are administered to largely healthy individuals over long periods. The risk-benefit and cost-benefit ratios are more likely to be unfavourable, making treatment decisions difficult. Drug trials provide insufficient information for treatment decisions, as they are conducted on highly selected populations over short durations, estimate only relative benefits of treatment and offer little information on risks and costs. Epidemiological modelling is a method of combining evidence from observational epidemiology and clinical trials to assist in clinical and health policy decision-making. It can estimate absolute benefits, risks and costs of long-term preventive strategies, and thus allow their precise targeting to individuals for whom they are safest and most cost-effective. Epidemiological modelling also allows explicit information about risks and benefits of therapy to be presented to patients, facilitating informed decision-making.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.