The National Latino and Asian American Study (NLAAS) II supplies mental health service providers and policy makers with the best available data on the correlates of psychiatric disorders in ethnically diverse populations and racial/ethnic disparities in mental health service use.

Building on the work of the original National Latino and Asian American Study (NLAAS), the goal of the NLAAS II is to supply mental health service providers and policy makers with the best available data on the correlates of psychiatric disorders in ethnically diverse populations and racial/ethnic disparities in mental health service use. These findings can be used to target resources, develop coherent public policies, and inform guidelines aimed at making mental health prevention and treatment services more responsive and sensitive to the needs of ethnic/racial minorities.

The NLAAS II is a three-year collaborative study seeking to identify and investigate the risk of psychiatric illness and mental health service disparities among Asian Americans and Latinos as compared to non-Latino Whites and African Americans. We will use recently collected data from the NLAAS, a national psychiatric epidemiologic study conducted to measure psychiatric disorders and mental health service usage in a representative sample of Asians and Latinos, and the National Comorbidity Survey Replication (NCS-R) and the National Survey of African American Life (NSAL). The combined NLAAS/NCS-R/NSAL data are the best available to address critical questions regarding psychiatric risk differences for Asian and Latino groups as compared to non-Latino Whites and other minorities, the level of service disparities, and the identification of geographic areas that we refer to as service disparities “hot spots.”

AIMS:

  • Aim 1: Use combined data from the NLAAS and the NCS-R to: compare prevalence of psychiatric disorders and mental health service use among Latinos, Asian-Americans, and non-Latino Whites; investigate hypotheses related to the correlates of illness and mental health services; and assess bias in psychiatric prevalence rates. We will first estimate the differences in prevalence and service use rates among Latinos, Asian-Americans, African Americans and non-Latino Whites. Next, we will investigate whether certain correlates of illness (e.g., family support, ethnic and racial diversity in community) and mental health service use (e.g., insurance, symptom levels) differ for Latinos and Asian Americans compared to non-Latino Whites and African Americans. We will also explore potential bias in reported psychiatric prevalence rates.
  • Aim 2: Apply the Institute of Medicine definition of disparities to distinguish between differences and Disparities when comparing mental health services utilization by Latino, Asian American, African Americans and non-Latino White populations. Quantify disparities in services utilization, and identify potential mechanisms underlying services disparitiesIn order to target resources and develop effective policy solutions to the problems of disparities, it is critical to accurately estimate these disparities at a national level. In this aim, we carefully estimate the extent of mental health service disparities using innovative methods to adjust for differences between Asians/Latinos/African Americans and non-Latino Whites in mental and physical health status and preferences regarding mental health treatment. We also explore the role of health care system factors as mechanisms of service disparities.
  • Aim 3: Apply methods from spatial epidemiology to the geography of disparities in mental health services use between Asian Americans, Latinos and non-Latino Whites. Identify “hot spots” of disparities at the Metropolitan Statistical Area (MSA) level by ranking MSAs according to their performance on disparities. Investigate factors at the health care system level that are associated with high and low performing MSAs. Policymakers need information on the geographic distribution of mental health service disparities in the US in order to prioritize and focus their efforts to ameliorate disparities. We propose to apply epidemiologic methods widely used to analyze disease clustering to the analysis of service disparities. We plan to rank MSAs based on their level of disparities and consider system-level factors that may be linked to performance of MSAs in terms of service disparities.