134 research outputs found
Domestic Violence Against Single, Never-Married Women in the Occupied Palestinian Territory Assaf
No full textBehaviour Risk Factor Surveillance Data Analysis using Time-Varying Coefficient Models: Application to Smokers in Italy
No full textApplication of the varying coefficient model to the behaviour risk factor surveillance data in Italy: a study of changing smoking prevalence among sub-populations
No full textBehaviour risk factor surveillance (BRFS) data can be an important source of information for studying changes in various health outcomes and risk factors. Results obtained from surveillance data analysis are vital for informing health policy interventions, particularly with regards to evolutionary aspects. The objective of this analysis was to recommend a method that can be used for analysing trends in the association among variables from large public health data sets. This was demonstrated by examining the changing effects of various covariates, representing different sub-populations, on smoking status over time
Behaviour Risk Factor Surveillance Data Analysis Using Varying Coefficient Models
No full textThere is a high potential of information available in Behaviour Risk Factor Surveillance (BRFS) data, and especially for studying trends, as these data collect information in an ongoing and almost continuous manner for long periods of time. In order to account for the complex and dynamic relationships between the variables and avoid the aggregation of measures so as not to lose information in variability, the use of varying coefficient models with non-parametric techniques have been studied. These models allow the study of the trends and inter-relationships in the effects of the variables on the outcome of interest either over time or space, therefore providing valuable information for health policy interventions.
A comparison of the possible estimation techniques, using the Italian surveillance data, has resulted in the selection of P-splines for estimation due to the flexibility in their use and the faster computation times. This estimation method was applied for a time varying coefficient model for a smoking status outcome variable using Italian surveillance data, and a time varying coefficient model for an obesity status outcome variable using U.S.A. surveillance data. The results of these models provide coefficient plots in which one can observe which subgroups of the population have an effect on the outcome which is changing over time. A spatial varying coefficient model was also studied for one point in time using smoothing spline estimation with tensor product smooths, and the maps produced from this model were able to show how the probabilities of the outcome variable (obesity) are changing across the counties of a U.S. state within each population subgroup. The strengths and limitations of these methods are discussed, as well as recommendations for further research such as the study of a spatial-temporal model using health surveillance data. Notwithstanding few limitations, the varying coefficient model represents an effective approach proving to produce interesting results (not accessible with the usual standard epidemiological approach) in this particular field of application and with BRFS data
Analysing behavioural risk factor surveillance data by using spatially and temporally varying coefficient models
No full textBackground\ud
\ud
Behaviour risk factor surveillance (BRFS) data can be an important source of information for studying changes in various health outcomes and risk factors. Results obtained from surveillance data analysis are vital for informing health policy interventions, particularly with regards to evolutionary aspects. The objective of this analysis was to recommend a method that can be used for analysing trends in the association among variables from large public health data sets. This was demonstrated by examining the changing effects of various covariates, representing different sub-populations, on smoking status over time.\ud
Methods\ud
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In our work, we propose the use of varying coefficient models (VCM) with non-parametric techniques to catch the dynamics of the evolutionary processes under study. This is a useful method, which allows coefficients to vary with time using smooth functions. Italian BRFS data from 2008-2012 was used with a sample size of 185,619 observations. In the application, a time VCM is fit for a smoking status binary outcome variable using the P-spline estimation method. The model includes ten independent variables comprising socio-demographic, health risk and behaviour variables.\ud
Results\ud
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The VCM fit for the data indicates that the coefficients for some of the categories for the age and the alcohol consumption variables varied with time. The main results show that Italians aged 18-29 and 40-49 had higher odds of being smokers compared to those aged 60-69; however, these odds significantly decreased in the period 2008-2012. In addition, those who do not drink had lower odds for being a smoker compared to high risk drinkers and these odds decreased further during the observation period.\ud
Conclusion\ud
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The application of the VCM to the BRFS data in Italy has shown that this method can be useful in detecting which sub-populations require interventions. Although the results have shown a decrease in the odds of being a smoker for certain age groups and non-drinkers, other sub-populations have not decreased their odds and health inequalities remain. This observation indicates that efforts and interventions are still required to target these non-changing sub-populations in order to modify their smoking behaviour
Hegemonic Frames in Mainstream Coverage on Palestine: A Case Study of Shireen Abu Akleh's Killing
No full textThis thesis examines the mainstream media's initial coverage of the killing of Palestinian-American Al Jazeera journalist, Shireen Abu Akleh, by Israeli occupation forces in May 2022. The initial reports on her murder failed to identify Israel as the responsible party, despite witness accounts affirming their involvement. Using Greg Shupak's frames prevalent in media coverage of Israel/Palestine, this paper conducts a content analysis of the preliminary reports issued by prominent mainstream media agencies to argue that the biased coverage of the tragic killing of Shireen Abu Akleh is a consequence of dominant frames that facilitate hegemony in journalism. Through this case study, this thesis illuminates the ways hegemonic frames shape mainstream media coverage of Palestine and continue to perpetuate the inaccurate portrayal of Israel's occupation and colonization
Analyzing disparity trends for health care insurance coverage among non-elderly adults in the US: evidence from the Behavioral Risk Factor Surveillance System, 1993-2009
No full textTo explore the changing disparities in access to health care insurance in the United States using time-varying coefficient models
Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009
No full textRe-evaluating Mabo: the case for native title reform to remove discrimination and promote economic opportunity
No full textThis paper seeks to reanalyse the Mabo case from the point of view of non-discrimination. It argues that the Mabo judgment may have been discriminatory in finding that pre-existing entitlements in surviving native title are restricted to the limited range of activities that can be proven by reference to traditional law and custom and that native title fails as a means of improving the economic and social opportunities of Indigenous Australians because of these restrictions. It suggests that native title law should be reformed on the basis of possession to recognise Indigenous peoples’ full and beneficial ownership of their land where this has not been extinguished.
The allocation of property rights to Indigenous people should not be limited by misguided and discriminatory assumptions about Indigenous culture and custom. About the Author Shireen Morris is the Constitutional Reform Research Fellow at Cape York Institute for Policy and Leadership. Her areas of research work include constitutional reform, racial discrimination, native title and, more recently, family violence and child reunification in Indigenous communities
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