Predictors of depression among older African American cancer patients.
BACKGROUND
Depression is becoming an increasing concern in cancer patients because of its impact on quality of life. Although risk factors of having depression have been examined in the literature, there has been no research examining these factors in older African American cancer patients.


OBJECTIVE
This study explores the demographic and illness-related risk factors in older African American cancer patients.


METHODS
Two hundred eighty-three patients were recruited from outpatient oncology clinics. These older African American patients completed a questionnaire that included the Geriatric Depression Scale as well as sociodemographic characteristics and medical information. chi2 Tests, trend tests, and logistic regression were used to identify the demographic and illness-related factors that predict depression in the sample.


RESULTS
The overall prevalence of depression in the sample was 27.2%. Younger age (<65 years), employment status, proximity to family, and multiple symptoms due to cancer or treatment were independent predictors of depression.


CONCLUSIONS
This study represents the first attempt to describe the risk factors of depression within older African American cancer patients. Findings indicate a high prevalence of depression in African American cancer patients which can be attributed to identifiable risk factors.


CONCLUSIONS
An understanding of the risk factors associated with depression can be used to identify those cancer patients at risk for depression and initiate early interventions to improve psychological outcomes and lessen the potential burden of cancer on these patients.
University of North Carolina, School of Nursing, Chapel Hill, NC 27599-7460, USA.
Mansi
M
Agarwal
Jill B
JB
Hamilton
Charles E
CE
Moore
Jamie L
JL
Crandell
D000223:Adaptation, Psychological; D001741:Black or African American / Q000208:ethnology / Q000706:statistics & numerical data; D000368:Aged / Q000523:psychology / Q000706:statistics & numerical data; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001294:Attitude to Health / Q000208:ethnology*; D016009:Chi-Square Distribution; D003863:Depression / Q000175:diagnosis / Q000208:ethnology* / Q000209:etiology; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D009369:Neoplasms / Q000150:complications* / Q000208:ethnology; D015404:Nursing Methodology Research; D015995:Prevalence; D011569:Psychiatric Status Rating Scales; D018570:Risk Assessment; D012307:Risk Factors; D012959:Socioeconomic Factors; D015144:Southeastern United States / Q000453:epidemiology; D011795:Surveys and Questionnaires