Using random forest to identify longitudinal predictors of health in a 30-year cohort study

Figures

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  Figure 1. Flowchart of study participants. 1 Roughly two-third of the participants from round 1 were randomly selected and re-invited to participate in round 2.

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  Figure 2. Summary of the six analysis steps.

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  Figure 3. Examples of average trajectories over time of a demographic (a), a lifestyle (b), an environmental (c), and a biological (d) exposure for those with good (solid green line) and poor (dashed blue line) perceived health status at round 6.

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  Figure 4. Variable importance ranking of the 30 most important exposures in predicting self-perceived health. The x-axis displays the mean decrease in accuracy that occurs when a particular exposure is permuted randomly in the random forest. AUE, Area-Under-the-Exposure; BMI, body mass index; BP, blood pressure; LPA, leisure time physical activity; r5, round 5; trend, Trend-of-the-Exposure; WHR, waist/hip ratio.

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  Figure 5. Exposure selection through cross-validation showing the prediction performance (Area-Under-the-Curve, AUC) (y-axis) of the model using a particular number of top-ranked exposures (x-axis). The dotted gray line represents the optimum number of exposures to select (q = 9).

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  Figure 6. Partial dependence plots (PDPs) of the relation between predictors of self-perceived health and poor self-perceived health. The dotted gray line represents the reference value, i.e. the predicted outcome corresponds to the prevalence of poor perceived health in the total population at round 6 (0.16). AUE, Area-Under-the-Exposure; BMI, body mass index; r5, round 5; WHR, waist/hip ratio.