Cardiovascular Disease among Asians and Pacific Islanders (CASPER)
A collaboration with Kaiser Hawaii
Cardiovascular disease (CVD) is the leading cause of death in the U.S., with total costs (including hypertension) of nearly $300 billion in 2008. The progression of CVD occurs over many years and is influenced by a series of demographic, clinical and psychosocial factors that vary across populations. In the U.S., these factors are poorly understood among Asians and Pacific Islanders. This is troubling because Asians are now the fastest growing minority population in the U.S., having increased by 43% in the past decade from 10.2 million to 14.7 million.Similarly, Native Hawaiian and other Pacific Islander populations have increased by more than 35% during this same time period. While Asian populations in the U.S. are commonly thought to be healthier than other minority groups and Non-Hispanic Whites, emerging research suggests that some Asian subgroups and Pacific Islanders might be at higher risk for CVD and associated poor outcomes. With such population growth, the health of these populations will have an increasing impact upon future U.S. health care needs and costs.
One reason this knowledge gap has persisted is the use of the broad “API” (Asian and Pacific Islander) or simply “Asian” designation in health research. This designation obscures important differences among the various API subgroups that are associated with CVD prevalence and outcomes, , including body mass index; socioeconomic status; smoking, diet, and other health behaviors; and level of acculturation in the U.S. Furthermore, limited evidence suggests there is as much as a six-fold difference among API subpopulations in rates of CVD. Previous studies, for example, show age-adjusted prevalence of CVD among API subpopulations ranging from 1.7% to 5.2%; stroke from 0.3% to 1.8%; and peripheral vascular disease from 0.9% to 3.4%. While the reasons for these wide differences remain largely unknown, very few well-designed studies have examined risk factors for CVD prevalence and outcomes among disaggregated API subpopulations. In addition, Pacific Islanders (50%) and Asians (15%) are among the most likely Americans to report belonging to more than one race. Although the recent growth in mixed-race populations is expected to continue, there is currently no information available about CVD among mixed-race populations.
To fill this important gap in knowledge about health disparities among API, we will measure CVD prevalence and outcomes among 9 well-defined API populations. Our multi-disciplinary team will comprehensively assess the role of demographic, clinical and psychosocial factors in explaining observed differences in CVD prevalence and outcomes. A better understanding of the underlying and potentially modifiable factors contributing to the health disparities experienced by these groups is critical to designing and implement effective intervention strategies to reduce CVD mortality and morbidity among these populations.
1. National Institutes of Health NIH, Lung and Blood Institute. Morbidity & Mortality: 2012 Chart Book on Cardiovascular, Lung, and Blood Diseases. February 2012.
2. Humes K.R. JNA, Ramirez R.R. Overview of Race and Hispanic Origin: 2010: U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau; 2011.
3. Holland AT, Palaniappan LP. Problems with the collection and interpretation of asian-american health data: omission, aggregation, and extrapolation. Ann Epidemiol. 2012;22(6):397-405.
4. Holland AT, Wong EC, Lauderdale DS, Palaniappan LP. Spectrum of cardiovascular diseases in Asian- American racial/ethnic subgroups. Ann Epidemiol. 2011;21(8):608-614.
Aim 1: Describe differences in the prevalence of CVD among Asian, Pacific Islander, and mixed-race API subpopulations.
Aim 2: Determine whether demographic, clinical and psychosocial factors explain observed differences in CVD prevalence among these populations.
Aim 3: Describe differences in secondary CVD outcomes and quality of life, and determine whether demographic, clinical and psychosocial factors explain observed differences in these variables.
Latha Palaniappan, M.D., M.S.
Beth Waitzfelder, M.D.