The societal benefits of reducing six behavioural risk factors : an economic modelling study from Australia

Background
A large proportion of disease burden is attributed to behavioural risk factors. However, funding for public health programs in Australia remains limited. Government and non-government organisations are interested in the productivity effects on society from reducing chronic diseases. We aimed to estimate the potential health status and economic benefits to society following a feasible reduction in the prevalence of six behavioural risk factors: tobacco smoking; inadequate fruit and vegetable consumption; high risk alcohol consumption; high body mass index; physical inactivity; and intimate partner violence.
Methods
Simulation models were developed for the 2008 Australian population. A realistic reduction in current risk factor prevalence using best available evidence with expert consensus was determined. Avoidable disease, deaths, Disability Adjusted Life Years (DALYs) and health sector costs were estimated. Productivity gains included workforce (friction cost method), household production and leisure time. Multivariable uncertainty analyses and correction for the joint effects of risk factors on health status were undertaken. Consistent methods and data sources were used.
Results
Over the lifetime of the 2008 Australian adult population, total opportunity cost savings of AUD2,334 million (95% Uncertainty Interval AUD1,395 to AUD3,347; 64% in the health sector) were found if feasible reductions in the risk factors were achieved. There would be 95,000 fewer DALYs (a reduction of about 3.6% in total DALYs for Australia); 161,000 less new cases of disease; 6,000 fewer deaths; a reduction of 5 million days in workforce absenteeism; and 529,000 increased days of leisure time.
Conclusions
Reductions in common behavioural risk factors may provide substantial benefits to society. For example, the total potential annual cost savings in the health sector represent approximately 2% of total annual health expenditure in Australia. Our findings contribute important new knowledge about productivity effects, including the potential for increased household and leisure activities, associated with chronic disease prevention. The selection of targets for risk factor prevalence reduction is an important policy decision and a useful approach for future analyses. Similar approaches could be applied in other countries if the data are available.

Family relationship quality and early alcohol use : evidence for gender-specific risk processes

Objective: Family characteristics (relationship quality, parental behaviors, and attitudes relating to alcohol use) are known to influence alcohol use in the mid-teen years, and there is evidence that family characteristics have different influences on mid-teen girls versus boys. This study examined child gender differences in the association of family relationship quality, parental disapproval of children's alcohol use, and parental alcohol use with early adolescent alcohol use.

Method: Grade 6 and 8 students (modal age 11 and 13, respectively; N = 6,837; 52.6% female) were recruited from 231 schools across three Australian states. Hypotheses were tested using two-level ordinal logistic regression (individuals nested within schools). The main dependent measure was lifetime frequency of early adolescent alcohol consumption. Independent variables included mother's/father's alcohol use, closeness, conflict, and disapproval of adolescent alcohol use. Control variables included sensation seeking, peer alcohol use, and socioeconomic disadvantage.

Results: The key findings were that for the young age group (Grade 6), emotional closeness to the parent of the opposite sex was protective. Family conflict was associated with females' drinking in both age groups but not males' drinking.

Conclusions: There was evidence of gender differences in the epidemiology of family relationship quality and early alcohol use. Social developmental models may need revision to account for these child gender differences. Gender-specific family dynamics may be an important consideration for family-oriented prevention strategy.

Modelling optimal risk allocation in PPP projects using artificial neural networks

This paper aims to establish, train, validate, and test artificial neural network (ANN) models for modelling risk allocation decision-making process in public-private partnership (PPP) projects, mainly drawing upon transaction cost economics. An industry-wide questionnaire survey was conducted to examine the risk allocation practice in PPP projects and collect the data for training the ANN models. The training and evaluation results, when compared with those of using traditional MLR modelling technique, show that the ANN models are satisfactory for modelling risk allocation decision-making process. The empirical evidence further verifies that it is appropriate to utilize transaction cost economics to interpret risk allocation decision-making process. It is recommended that, in addition to partners' risk management mechanism maturity level, decision-makers, both from public and private sectors, should also seriously consider influential factors including partner's risk management routines, partners' cooperation history, partners' risk management commitment, and risk management environmental uncertainty. All these factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects.

Credit risk of interest rate swaps : a comparative study of CIR and Monte Carlo simulation approach

This paper compares the credit risk profile for two types of model, the Monte Carlo model used in the existing literature, and the Cox, Ingersoll and Ross (CIR) model. Each of the profiles has a concave or hump-backed shape, reflecting the amortisation and diffusion effects. However, the CIR model generates significantly different results. In addition, we consider the sensitivity of these models of credit risk to initial interest rates, volatility, maturity, kappa and delta. The results show that the sensitivities vary across the models, and we explore the meaning of that variation.

Takeaway food consumption and cardio-metabolic risk factors in young adults

Background/objectives: Takeaway food consumption is positively associated with adiposity. Little is known about the associations with other cardio-metabolic risk factors. This study aimed to determine whether takeaway food consumption is associated with fasting glucose, insulin, lipids, homeostasis model assessment (HOMA) and blood pressure.

Subjects/methods: A national sample of 1896, 26–36 year olds completed a questionnaire on socio-demographics, takeaway food consumption, physical activity and sedentary behaviour. Waist circumference and blood pressure were measured, and a fasting blood sample was taken. For this analysis, takeaway food consumption was dichotomised to once a week or less and twice a week or more. Linear regression was used to calculate differences in the adjusted mean values for fasting lipids, glucose, insulin, HOMA and blood pressure. Models were adjusted for age, employment status, leisure time physical activity and TV viewing.

Results: Compared with women who ate takeaway once a week or less, women who ate takeaway twice a week or more had significantly higher adjusted mean fasting glucose (4.82 vs 4.88 mmol/l, respectively; P=0.045), higher HOMA scores (1.27 vs 1.40, respectively, P=0.034) and tended to have a higher mean fasting insulin (5.95 vs 6.45 mU/l, respectively, P=0.054). Similar associations were observed for men for fasting insulin and HOMA score, but the differences were not statistically significant. For both women and men adjustment for waist circumference attenuated the associations.

Conclusion: Consuming takeaway food at least twice a week was associated with cardio-metabolic risk factors in women but less so in men. The effect of takeaway food consumption was attenuated when adjusted for obesity.

Do parents’ and children’s concerns about sports safety and injury risk relate to how much physical activity children do?

Objective To see whether concerns about injury risk relate to children's physical activity (PA).
Methods Two cohorts were recruited from 19 Australian schools and assessed in 2001 (T1), 2004 (T2) and 2006 (T3). The younger (n=162) was assessed at 6, 9 and 11years old, and the older (n=259) at 11, 14 and 16 years old. At T1 and T2, parents of the younger cohort reported on fear of child being injured, and whether child would be at risk of injury if they played organised sport; the older cohort self-reported injury fear. Accelerometers assessed PA at each time point. Linear regression models examined cross-sectional associations, and also associations between T1 injury fear and risk and T2 PA, and T2 injury fear and risk and T3 PA.
Results In the younger cohort at T2 (9 years), fear and risk were both negatively associated with moderate to vigorous PA (MVPA) (β=−0.17, 95% CI −0.30 to −0.03 and β=−0.26, 95% CI −0.41 to −0.10) and also vigorous PA (VPA). Fear was also associated with moderate PA (MPA). For the older cohort at T1, injury fear was negatively associated with MVPA (β=−0.21, 95% CI −0.35 to −0.07) and also MPA and VPA. Parental perception of risk at T1 (6 years) was negatively associated with children's MPA at T2 (9 years) (β=−0.17, 95% CI −0.32 to −0.02). Sex did not moderate any association.
Conclusions Younger children and their parents need to know which sports have low injury risks. Some children may need increased confidence to participate.

Age at quitting smoking as a predictor of risk of cardiovascular disease incidence independent of smoking status, time since quitting and pack-years

Background: Risk prediction for CVD events has been shown to vary according to current smoking status, pack-years smoked over a lifetime, time since quitting and age at quitting. The latter two are closely and inversely related. It is not known whether the age at which one quits smoking is an additional important predictor of CVD events. The aim of this study was to determine whether the risk of CVD events varied according to age at quitting after taking into account current smoking status, lifetime pack-years smoked and time since quitting.
Findings. We used the Cox proportional hazards model to evaluate the risk of developing a first CVD event for a cohort of participants in the Framingham Offspring Heart Study who attended the fourth examination between ages 30 and 74 years and were free of CVD. Those who quit before the median age of 37 years had a risk of CVD incidence similar to those who were never smokers. The incorporation of age at quitting in the smoking variable resulted in better prediction than the model which had a simple current smoker/non-smoker measure and the one that incorporated both time since quitting and pack-years. These models demonstrated good discrimination, calibration and global fit. The risk among those quitting more than 5 years prior to the baseline exam and those whose age at quitting was prior to 44 years was similar to the risk among never smokers. However, the risk among those quitting less than 5 years prior to the baseline exam and those who continued to smoke until 44 years of age (or beyond) was two and a half times higher than that of never smokers.
Conclusions: Age at quitting improves the prediction of risk of CVD incidence even after other smoking measures are taken into account. The clinical benefit of adding age at quitting to the model with other smoking measures may be greater than the associated costs. Thus, age at quitting should be considered in addition to smoking status, time since quitting and pack-years when counselling individuals about their cardiovascular risk.

Framingham risk prediction equations for incidence of cardiovascular disease using detailed measures for smoking

Current prediction models for risk of cardiovascular disease (CVD) incidence incorporate smoking as a dichotomous yes/no measure. However, the risk of CVD associated with smoking also varies with the intensity and duration of smoking and there is a strong association between time since quitting and the risk of disease onset. This study aims to develop improved risk prediction equations for CVD incidence incorporating intensity and duration of smoking and time since quitting. The risk of developing a first CVD event was evaluated using a Cox’s model for participants in the Framingham offspring cohort who attended the fourth examination (1988–92) between the ages of 30 and 74 years and were free of CVD (n=3751). The full models based on the smoking variables and other risk factors, and reduced models based on the smoking variables and non-laboratory risk factors demonstrated good discrimination, calibration and global fit. The incorporation of both time since quitting among past smokers and pack-years among current smokers resulted in better predictive performance as compared to a dichotomous current/non-smoker measure and a current/quitter/never smoker measure. Compared to never smokers, the risk of CVD incidence increased with pack-years. Risk among those quitting more than five years prior to the baseline exam and within five years prior to the baseline exam were similar and twice as high as that of never smokers. A CVD risk equation incorporating the effects of pack-years and time since quitting provides an improved tool to quantify risk and guide preventive care.

The number of years lived with obesity and the risk of all-cause and cause-specific mortality

Background The role of the duration of obesity as an independent risk factor for mortality has not been investigated. The aim of this study was to analyse the association between the duration of obesity and the risk of mortality.

Methods A total of 5036 participants (aged 28–62 years) of the Framingham Cohort Study were followed up every 2 years from 1948 for up to 48 years. The association between obesity duration and all-cause and cause-specific mortality was analysed using time-dependent Cox models adjusted for body mass index. The role of biological intermediates and chronic diseases was also explored.

Results The adjusted hazard ratio (HR) for mortality increased as the number of years lived with obesity increased. For those who were obese for 1–4.9, 5–14.9, 15–24.9 and ≥25 years of the study follow-up period, adjusted HRs for all-cause mortality were 1.51 [95% confidence interval (CI) 1.27–1.79], 1.94 (95% CI 1.71–2.20), 2.25 (95% CI 1.89–2.67) and 2.52 (95% CI 2.08–3.06), respectively, compared with those who were never obese. A dose–response relation between years of duration of obesity was also clear for all-cause, cardiovascular, cancer and other-cause mortality. For every additional 2 years of obesity, the HRs for all-cause, cardiovascular disease, cancer and other-cause mortality were 1.06 (95% CI 1.05–1.07), 1.07 (95% CI 1.05–1.08), 1.03 (95% CI 1.01–1.05) and 1.07 (95% CI 1.05–1.11), respectively.

Conclusions The number of years lived with obesity is directly associated with the risk of mortality. This needs to be taken into account when estimating its burden on mortality.

The duration of obesity and the risk of type-2 diabetes

Objective The evidence for the association between obesity and the risk of type 2 diabetes has been derived mainly from the analysis of the degree of obesity. The role of the duration of obesity as an independent risk has not been fully explored. The objective of the present study was to investigate the association between the duration of obesity and the risk of type 2 diabetes.

Design Prospective cohort study.

Setting The Framingham Heart Study (FHS), follow-up from 1948 to 1998.

Subjects A total of 1256 FHS participants who were free from type 2 diabetes at baseline, but were obese on at least two consecutive of the study’s twenty-four biennial examinations, were included. Type 2 diabetes status was collected throughout the 48 years of follow-up of the study. The relationship between duration of obesity and type 2 diabetes was analysed using time-dependent Cox models, adjusting for a number of covariates.

Results The unadjusted hazard ratio (HR) for the risk of type 2 diabetes for men was 1·13 (95 % CI 1·09, 1·17) and for women was 1·12 (95 % CI 1·08, 1·16) per additional 2-year increase in the duration of obesity. Adjustment for sociodemographic variables, family history of diabetes, health behaviour and physical activity made little difference to these HR. For women the evidence of a dose–response relationship was less clear than for men, particularly for women with an older age at obesity onset.

Conclusions The duration of obesity is a relevant risk factor for type 2 diabetes, independent of the degree of BMI.

SAS macros for point and interval estimation of area under the receiver operating characteristic curve for non-proportional and proportional hazards Weibull models

Aims and objectives  For prediction of risk of cardiovascular end points using survival models the proportional hazards assumption is often not met. Thus, non-proportional hazards models are more appropriate for developing risk prediction equations in such situations. However, computer program for evaluating the prediction performance of such models has been rarely addressed. We therefore developed SAS macro programs for evaluating the discriminative ability of a non-proportional hazards Weibull model developed by Anderson (1991) and that of a proportional hazards Weibull model using the area under receiver operating characteristic (ROC) curve.

Method  Two SAS macro programs for non-proportional hazards Weibull model using Proc NLIN and Proc NLP respectively and model validation using area under ROC curve (with its confidence limits) were written with SAS IML language. A similar SAS macro for proportional hazards Weibull model was also written.

Results  The computer program was applied to data on coronary heart disease incidence for a Framingham population cohort. The five risk factors considered were current smoking, age, blood pressure, cholesterol and obesity. The predictive ability of the non-proportional hazard Weibull model was slightly higher than that of its proportional hazard counterpart. An advantage of SAS Proc NLP in terms of the example provided here is that it provides significance level for the parameter estimates whereas Proc NLIN does not.

Conclusion  The program is very useful for evaluating the predictive performance of non-proportional and proportional hazards Weibull models.

Fuzzy rule base assessment models : theoretical analyses and a case study

An assessment model is usually a mathematical model that produces a measuring index, in the form of a numerical score to a situation/object, with respect to the subject of measure. To allow a valid and useful comparison among various situations/objects according to their associated numerical scores to be made, two important properties, i.e., the monotone output property and output resolution properties, are essential in fuzzy inference-based assessment problems. In this paper, the conditions for a fuzzy assessment model to fulfill the monotone output property is investigated using a derivative approach. A guideline on how the input membership functions should be tuned is also provided. Besides, the output resolution property is defined as the derivative of the output of the assessment model with respect to the input, whereby the derivative should be greater than a minimum resolution. Based on the derivative, improvements to the output resolution property by refining the fuzzy production rules are suggested. A case study on the Bowles fuzzy RPN model to demonstrate the effectiveness of the properties is also included.

On the use of fuzzy inference techniques in assessment models : part II : industrial applications

In this paper, we study the applicability of the monotone output property and the output resolution property in fuzzy assessment models to two industrial Failure Mode and Effect Analysis (FMEA) problems. First, the effectiveness of the monotone output property in a single-input fuzzy assessment model is demonstrated with a proposed fuzzy occurrence model. Then, the usefulness of the two properties to a multi-input fuzzy assessment model, i.e., the Bowles fuzzy Risk Priority Number (RPN) model, is assessed. The experimental results indicate that both the fuzzy occurrence model and Bowles fuzzy RPN model are able to fulfill the monotone output property, with the derived conditions (in Part I) satisfied. In addition, the proposed rule refinement technique is able to improve the output resolution property of the Bowles fuzzy RPN model.

Safeguarding Australia from cyber-terrorism : a SCADA risk framework

Terrorist groups are currently using information and communication technologies (ICTs) to orchestrate their conventional attacks. More recently, terrorists have been developing a new form of capability within the cyber-arena to coordinate cyber-based attacks. This chapter identifies that cyber-terrorism capabilities are an integral, imperative, yet under-researched component in establishing, and enhancing cyber-terrorism risk assessment models for SCADA systems. This chapter examines a cyber-terrorism SCADA risk framework that has been adopted and validated by SCADA industry practitioners. The chapter proposes a high level managerial framework, which is designed to measure and protect SCADA systems from the threat of cyber-terrorism within Australia. The findings and results of an industry focus group are presented in support of the developed framework for SCADA industry acceptance.