Abstract

American Indian populations have often been considered to be at greater risk for major depressive episode than are other groups in the United States. The American Indian Service Utilization, Psychiatric Epidemiology, Risk and Protective Factors Project (AI-SUPERPFP), completed between 1997 and 1999, was designed to allow comparisons with the baseline National Comorbidity Survey (NCS), conducted in 1990-1992. The prevalence of lifetime and 12-month DSM-III-R major depressive episode was compared between the AI-SUPERPFP and NCS samples. A total of 3,084 tribal members (1,446 in a Southwest tribe [73.7% of eligible participants] and 1,638 in a Northern Plains tribe [76.8% of eligible participants]) age 15-54 years living on or near their home reservations were interviewed. An adaptation of the University of Michigan Composite International Diagnostic Interview and the NCS algorithm for diagnosis were used to estimate the prevalence of lifetime and 12-month major depressive episode in these groups. The prevalence estimates for lifetime and 12-month major depressive episode were substantially lower in the American Indian samples, compared to the NCS sample. Detailed analyses indicated differential endorsement of lifetime symptoms between the American Indian groups and the NCS participants. Furthermore, American Indians were substantially less likely than NCS participants to indicate that depressive symptoms had co-occurred during an episode lasting at least 2 weeks. The lifetime prevalence estimates based on the NCS algorithm ranged from 3.8% to 7.9% for men and women in the two tribes. The analogous rates based on an adapted AI-SUPERPFP algorithm ranged from 7.2% and 14.3%. Few tribe, age, and gender differences were found. The findings underscore the need for careful examination of diagnostic instruments cross-culturally. Adaptation of the NCS algorithm for diagnosis appears necessary for estimation of the prevalence of major depressive episode in the American Indian populations included in this study. In striving to better reflect the clinical diagnostic process in epidemiological and services research, careful consideration of the resulting complexity becomes increasingly critical.

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