Socioeconomic disadvantage and changes in health risk behaviours in Australia: 1989-90 to 2001

Objective. Lower socioeconomic status (SES) is associated in industrialized countries with unhealthy lifestyle characteristics, such as smoking, physical inactivity and being overweight or obese. This paper examines changes over time in the association between SES and smoking status, physical activity and being overweight or obese in Australia. Methods. Data were taken from three successive national health surveys in Australia carried out in 1989-90 (n = 54 576), 1995 (n = 53 828) and 2001 (n = 26 863). Participants in these surveys were selected using a national probability sampling strategy, and aggregated data for geographical areas are used to determine the changing association between SES and lifestyle over time. Findings. Overall, men had less healthy lifestyles, In 2001 inverse SES trends for both men and women showed that those living in lower SES areas were more likely to smoke and to be sedentary and obese, There were some important socioeconomic changes over the period 1989-90 to 2001. The least socioeconomically disadvantaged areas had the largest decrease in the percentage of people smoking tobacco (24% decrease for men and 12% for women) and the largest decrease in the percentage of people reporting sedentary activity levels (25% decrease for men and 22% for women). While there has been a general increase in the percentage over time of those who are overweight or obese, there is a modest trend for being overweight to have increased (by about 16% only among females) among those living in areas of higher SES. Conclusion. Socioeconomic inequalities have been increasing for several key risk behaviours related to health; this suggests that T specific population-based prevention strategies intended to reduce health inequalities are needed.

Ontological clarity and comprehension in health data models

Conceptual modeling forms an important part of systems analysis. If this is done incorrectly or incompletely, there can be serious implications for the resultant system, specifically in terms of rework and useability. One approach to improving the conceptual modelling process is to evaluate how well the model represents reality. Emergence of the Bunge-Wand-Weber (BWW) ontological model introduced a platform to classify and compare the grammar of conceptual modelling languages. This work applies the BWW theory to a real world example in the health arena. The general practice computing group data model was developed using the Barker Entity Relationship Modelling technique. We describe an experiment, grounded in ontological theory, which evaluates how well the GPCG data model is understood by domain experts. The results show that with the exception of the use of entities to represent events, the raw model is better understood by domain experts