Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach.
BACKGROUND
Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk.


METHODS
The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves.


RESULTS
The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors.


CONCLUSIONS
The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.
Batterham
Philip J
PJ
Centre for Mental Health Research, The Australian National University, Canberra, Australia. philip.batterham@anu.edu.au
Christensen
Helen
H
Mackinnon
Andrew J
AJ
D000328:Adult; D017677:Age Distribution; D000368:Aged; D001315:Australia / Q000453:epidemiology; D002318:Cardiovascular Diseases / Q000453:epidemiology; D003625:Data Collection / Q000706:statistics & numerical data; D003663:Decision Trees; D003865:Major Depressive Disorder / Q000453:epidemiology*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D015995:Prevalence; D011336:Probability; D018570:Risk Assessment; D012307:Risk Factors; D040242:Risk Reduction Behavior