Performance demonstration of SVR and MLR in a simple scenario (two-dimensional case).

<p>The black dots indicate actual simulation data set. The solid curve denotes SVR regress line and the dot line represents the MLR regression line. The simulation data set is randomly generated by MATLAB.</p

Correlation of measured 25(OH)D concentration (nmol/L) and predicted 25(OH)D concentration using (A) a multiple linear regression model; and (B) a radial basis function support vector regression model.

<p>Correlation of measured 25(OH)D concentration (nmol/L) and predicted 25(OH)D concentration using (A) a multiple linear regression model; and (B) a radial basis function support vector regression model.</p

Accuracy of predicted 25(OH)D score in each quintile of 25(OH)D concentration.

<p>Accuracy of predicted 25(OH)D score in each quintile of 25(OH)D concentration.</p

ROC curves of MLR and RBF SVR.

<p>ROC curves showing true-positive rates (sensitivity) plotted against the false-positive rate for different cut off points of the quantified components of MLR (gray diamonds) and RBF SVR (black circles). The points highlighted are 25(OH)D scores of 75 nmol/l for MLR and RBF SVR. The area under the curve is 0.79 and 0.87 for MLR and RBF SVR respectively.</p

Predicted 25(OH)D concentration and mean absolute difference between predicted and measured 25(OH)D level (nmol/L).

<p>RBF SVR, radial basis function support vector regression (nonlinear support vector regression).</p><p>MLR, multiple linear regression.</p><p>Mean absolute difference is the average of the absolute differences between the predicted and measured values.</p

Bland – Altman plots of measured 25(OH)D concentration compared to predicted scores from (A) a MLR model; (B) a RBF SVR model.

<p>The solid lines indicate the mean bias (middle line) and 95% limits of agreement (top and bottom lines). All measurements are in nmol/L.</p

Percentage of individuals classified by quintiles of measured 25(OH)D concentration and predicted 25(OH)D score.

<p>Percentage of individuals classified by quintiles of measured 25(OH)D concentration and predicted 25(OH)D score.</p

Recent studies using a multiple linear regression prediction model for 25(OH)D concentration.

<p>Recent studies using a multiple linear regression prediction model for 25(OH)D concentration.</p

Prevalence of cardiovascular disease risk profiles by region of birth and sex (fully adjusted).

<p>¹ PR, prevalence ratio, adjusted for age, education, income, private health insurance, marital status and location of residence</p><p>Prevalence of cardiovascular disease risk profiles by region of birth and sex (fully adjusted).</p

Cardiovascular Disease Risk Factor Profiles of 263,356 Older Australians According to Region of Birth and Acculturation, with a Focus on Migrants Born in Asia

<div><p>Risk factors for cardiovascular disease (CVD), such as obesity, diabetes, hypertension and physical inactivity, are common in Australia, but the prevalence varies according to cultural background. We examined the relationship between region of birth, measures of acculturation, and CVD risk profiles in immigrant, compared to Australian-born, older Australians. Cross-sectional data from 263,356 participants aged 45 and over joining the population-based 45 and Up Study cohort from 2006–2008 were used. Prevalence ratios for CVD risk factors in Australian- versus overseas-born participants were calculated using modified Poisson regression, adjusting for age, sex and socioeconomic factors and focusing on Asian migrants. The association between time resident in Australia and age at migration and CVD risk factors in Asian migrants was also examined. Migrants from Northeast (n = 3,213) and Southeast Asia (n = 3,942) had lower levels of overweight/obesity, physical activity and female smoking than Australian-born participants (n = 199,356), although differences in prevalence of overweight/obesity were sensitive to body-mass-index cut-offs used. Compared to Australian-born participants, migrants from Northeast Asia were 20–30% less likely, and from Southeast Asia 10–20% more likely, to report being treated for hypertension and/or hypercholesterolaemia; Southeast Asian migrants were 40–60% more likely to report diabetes. Northeast Asian-born individuals were less likely than Australian-born to have 3 or more CVD risk factors. Diabetes, treated hypertension and hypercholesterolaemia occurred at relatively low average body-mass-index in Southeast Asian migrants. The CVD risk factor profiles of migrants tended to approximate those of Australian-born with increasing acculturation, in both favourable (e.g., increased physical activity) and unfavourable directions (e.g., increased female smoking). Minimizing CVD risk in migrant populations may be achieved through efforts to retain the healthy facets of the traditional lifestyle, such as a normal body mass index and low prevalence of smoking in women, in addition to adopting healthy aspects of the host country lifestyle, such as increased physical activity.</p></div