Regular Research Article| Volume 30, ISSUE 9, P949-960, September 2022

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Risk Prediction Models for Depression in Community-Dwelling Older Adults


      • What is the primary question addressed by this study?
        Can we reliably identify older individuals at risk for depression?
      • What is the main finding of this study?
        Using selected information, the Manto Risk Prediction Models can predict the risk for developing of depression 2 years later with satisfactory accuracy. The streamlined Manto Risk Prediction Model is available for free public use through a web-based risk calculator (
      • What is the meaning of the finding?
        Estimating an individual's risk for developing late-life depression allows to target prevention strategies at an individual and a population-level.



      To develop streamlined Risk Prediction Models (Manto RPMs) for late-life depression.


      Prospective study.


      The Survey of Health, Ageing and Retirement in Europe (SHARE) study.


      Participants were community residing adults aged 55 years or older.


      The outcome was presence of depression at a 2-year follow up evaluation. Risk factors were identified after a literature review of longitudinal studies. Separate RPMs were developed in the 29,116 participants who were not depressed at baseline and in the combined sample of 39,439 of non-depressed and depressed subjects. Models derived from the combined sample were used to develop a web-based risk calculator.


      The authors identified 129 predictors of late-life depression after reviewing 227 studies. In non-depressed participants at baseline, the RPMs based on regression and Least Absolute Shrinkage and Selection Operator (LASSO) penalty (34 and 58 predictors, respectively) and the RPM based on Artificial Neural Networks (124 predictors) had a similar performance (AUC: 0.730–0.743). In the combined depressed and non-depressed participants at baseline, the RPM based on neural networks (35 predictors; AUC: 0.807; 95% CI: 0.80–0.82) and the model based on linear regression and LASSO penalty (32 predictors; AUC: 0.81; 95% CI: 0.79–0.82) had satisfactory accuracy.


      The Manto RPMs can identify community-dwelling older individuals at risk for developing depression over 2 years. A web-based calculator based on the streamlined Manto model is freely available at for use by individuals, clinicians, and policy makers and may be used to target prevention interventions at the individual and the population levels.

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