Income, Residence Location, and Depression Diagnosis among Older Adults in Six Middle Income Countries: Findings from the Study on Global AGEing and Adult Health (SAGE)
James J. Snodgrass, University of Oregon
Caroline Porter, University of Oregon
Geeta Eick, University of Oregon
Depression is increasingly recognized globally as a critical health issue; however, it is commonly untreated because barriers to health care access contribute to underdiagnosis. Few studies have considered the specific factors associated with underreporting. The present study examines older adults from China, Ghana, India, Mexico, Russia, and South Africa in order to compare depression diagnosis using self-report (SR) with identification based on a symptom-based algorithm and to consider the effects of income and residence location on diagnosis. Results indicate that more individuals are classified as depressed according to the symptom-based algorithm (p<0.001). A key finding is that the odds of being classified as depressed based on SR increased as income increased (p=0.012 in males; p=0.003 in females) while the odds of depression classification based on the algorithm decreased as income increased (p=0.006 in males; p<0.001 in females). This study highlights the importance of socioeconomic factors in the diagnosis of depression.