Characterising the extent of misreporting of high blood pressure, high cholesterol, and diabetes using the Australian Health Survey.

BACKGROUND: Measuring and monitoring the true prevalence of risk factors for chronic conditions is essential for evidence-based policy and health service planning. Understanding the prevalence of risk factors for cardiovascular disease (CVD) in Australia relies heavily on self-report measures from surveys, such as the triennial National Health Survey. However, international evidence suggests that self-reported data may substantially underestimate actual risk factor prevalence. This study sought to characterise the extent of misreporting in a large, nationally-representative health survey that included objective measures of clinical risk factors for CVD. METHODS: This study employed a cross-sectional analysis of 7269 adults aged 18 years and over who provided fasting blood samples as part of the 2011-12 Australian Health Survey. Self-reported prevalence of high blood pressure, high cholesterol and diabetes was compared to measured prevalence, and univariate and multivariate logistic regression analyses identified socio-demographic characteristics associated with underreporting for each risk factor. RESULTS: Approximately 16 % of the total sample underreported high blood pressure (measured to be at high risk but didn't report a diagnosis), 33 % underreported high cholesterol, and 1.3 % underreported diabetes. Among those measured to be at high risk, 68 % did not report a diagnosis for high blood pressure, nor did 89 % of people with high cholesterol and 29 % of people with high fasting plasma glucose. Younger age was associated with underreporting high blood pressure and high cholesterol, while lower area-level disadvantage and higher income were associated with underreporting diabetes. CONCLUSIONS: Underreporting has important implications for CVD risk factor surveillance, policy planning and decisions, and clinical best-practice guidelines. This analysis highlights concerns about the reach of primary prevention efforts in certain groups and implications for patients who may be unaware of their disease risk status.

Regional variation in cardiovascular mortality in Australia 2009-2012: the impact of remoteness and socioeconomic status.

OBJECTIVE: To assess the extent to which socioeconomic status (SES) contributes to geographic disparity in cardiovascular disease (CVD) mortality. METHODS: An ecological study assessed the association between remoteness and CVD mortality rates, and the mediating effect of SES on this relationship, using Australia-wide data from 2009 to 2012. RESULTS: Socioeconomic status explained approximately one-quarter of the increased CVD mortality rates for females in inner and outer regional areas, and more than half of the increased CVD mortality rates in inner regional and remote/very remote areas for males, compared to major cities. After allowing for the mediating effect of SES, females living in inner regional areas and males living in remote/very remote areas had the greatest CVD mortality rates (Mortality Rate Ratio: 1.12, 95%CI 1.07-1.17; MRR: 1.15, 95%CI 1.05-1.25, respectively) compared to those in major cities. CONCLUSION: Socioeconomic status explained a substantial proportion of the association between where a person resides and CVD mortality rates; however, remoteness has an effect above and beyond SES for a number of subpopulations. Implications for public health: This study highlights the need to focus on both socioeconomic disadvantage and accessibility to reduce CVD mortality in regional and remote Australia.

Comparison between measured and perceived weight status in a nationally representative sample of Australian adults.

BACKGROUND: Many individuals may not accurately perceive whether their weight status poses a health risk. This paper aimed to determine how accurately Australians perceived their weight status compared to objective measurements, and to determine what factors were associated with underestimating weight status. METHODS: Participants were 7947 non-pregnant adults from the 2011 to 2012 Australian National Nutrition and Physical Activity Survey, with complete data for self-reported and measured weight status. Multivariate logistic regression was used to examine associations between individual characteristics and accuracy of perceived weight status. RESULTS: Overall, 25.5% of the sample underestimated and 3.8% overestimated their weight status. Men were almost twice as likely as women to underestimate (34.0% vs 17.7%, p<0.001). In both sexes, underestimating weight status was strongly associated with higher waist circumference, satisfaction with weight and older age. In men, underestimation was associated with low education levels and being on a diet, and in women, underestimating weight status was associated with being born overseas and area-level disadvantage. CONCLUSIONS: At least a quarter of the adult population misperceives their weight status as healthy when in fact they are at increased risk of morbidity and mortality due to overweight and obesity. This may present a major barrier to prevention efforts.

Quantifying the role of modifiable risk factors in the differences in cardiovascular disease mortality rates between metropolitan and rural populations in Australia: a macrosimulation modelling study.

OBJECTIVES: The study aimed (1) to quantify differences in modifiable risk factors between urban and rural populations, and (2) to determine the number of rural cardiovascular disease (CVD) and ischaemic heart disease (IHD) deaths that could be averted or delayed if risk factor levels in rural areas were equivalent to metropolitan areas. SETTING: National population estimates, risk factor prevalence, CVD and IHD deaths data were analysed by rurality using a macrosimulation Preventable Risk Integrated Model for chronic disease risk. Uncertainty analysis was conducted using a Monte Carlo simulation of 10 000 iterations to calculate 95% credible intervals (CIs). PARTICIPANTS: National data sets of men and women over the age of 18 years living in urban and rural Australia. RESULTS: If people living in rural Australia had the same levels of risk factors as those in metropolitan areas, approximately 1461 (95% CI 1107 to 1791) deaths could be delayed from CVD annually. Of these CVD deaths, 793 (95% CI 506 to 1065) would be from IHD. The IHD mortality gap between metropolitan and rural populations would be reduced by 38.2% (95% CI 24.4% to 50.6%). CONCLUSIONS: A significant portion of deaths from CVD and IHD could be averted with improvements in risk factors; more than one-third of the excess IHD deaths in rural Australia were attributed to differences in risk factors. As much as two-thirds of the increased IHD mortality rate in rural areas could not be accounted for by modifiable risk factors, however, and this requires further investigation.