Recent advances in depression. Where are we going?

What is this thing called “SAD”? A critique of the concept of seasonal affective disorder

Background– Seasonal Affective Disorder (SAD) is supposed to be caused by lack of daylight in winter. Yet the population of Northern Norway, living without sun for two winter months, does not spontaneously complain about depression during the dark period.Aims– To summarize research bearing upon the validity of the concept of SAD.Method– Review of relevant literature concerning the epidemiology of SAD and the questionnaire developed to measure it in general populations, the Seasonal Pattern Assessment Questionnaire (SPAQ).Results– Large population studies from northern Norway do not point to a higher prevalence of depression in winter than expected in any other general population. The psychometric properties of SPAQ are rather poor, and the diagnosis of SAD based on SPAQ bears little relationship to a meaningful concept of depression.Conclusions– Seasonal Affective Disorder is not a valid medical construct. Instead, “Recurrent depression with seasonal pattern” as defined in the DSM-IV and the ICD-10 should be used as terms. However, more research is needed to establish whether it is at all fruitful to single out such a subtype of recurrent depression.

Declaration of Interest: None.

Genetic opportunities for psychiatric epidemiology: on life stress and depression

AIMS

Genetics can offer new resources to epidemiology. This review will consider recent findings regarding the link between stress and depression as an example to illustrate the added value of employing genetics in epidemiological studies.

METHODS

Systematic review of medical and psychological databases.

RESULTS

Genetic and environmental factors may correlate. This suggests the potential for genetic mediation of the exposure to the environment. Gene-environment correlations can help epidemiologists to better understand causal pathways and suggest effective therapeutic strategies. Genetic and environmental factors may also interact. This suggests the potential for genetic modification of environmental effects on disease risk. Gene-environment interactions can help epidemiologists to identify vulnerable individuals and strata-specific environmental effects.

CONCLUSIONS

New models of disease based on the interplay between genes and environments are providing epidemiology with a new set of testable hypotheses that will advance our understanding of mental health and illness.