South Florida: A National Microcosm of Diversity and Health Disparities
Brooten, Dorothy, Youngblut, JoAnne M., Journal of Cultural Diversity
Abstract: South Florida is a microcosm of diversity that reflects a changing national population. The purpose of this paper is to examine some common health status indicators in the four counties that comprise South Florida. The researchers look at birthweight, neonatal and infant death rates, receipt of prenatal care, major causes of death, availability of health care facilities and services, and expenditures for health. Data indicate that, of the four counties, the most affluent has the worst health indicators, and the least affluent - with the highest proportion of minority residents - has some of the best health status indicators. The researchers provide implications for practitioners and future research.
Key Words: Health Disparities, Health Status Indicators, Minorities
South Florida is a microcosm of diversity that in many ways reflects a changing national population. South Florida's large and varied minority and underserved populations serve as a natural laboratory for examining the challenges in providing health care for diverse cultural groups, including those who are newly immigrated and non-English speaking.
South Florida is composed of four diverse counties: Miami-Dade, Broward, Palm Beach, and Monroe. Miami-Dade is the largest county, with a population of over 2.3 million. Hispanics of various ethnic backgrounds comprise the largest group in Miami-Dade County (Florida Department of Health, 2005f). Fifty-one percent of the county's residents are foreign-born, and 68% are non-English speaking at home (Dyer, 2003). The greatest new growth in Miami-Dade County represents immigrants from other countries as well as some migrants (largely retirees) from within the U.S. According to Kroll (2004), over the last five years, 238,000 people have arrived in Miami-Dade County from abroad. In 2000, the unemployment rate was 8.7% compared to a state-wide rate of 5.6% (U.S. Census Bureau, 2000).
Broward County is the second largest South Florida county with a population of over 1.7 million (Florida Department of Health/ 2005a). Broward County lies geographically between Miami-Dade County to the south and Palm Beach County to the north. Fort Lauderdale is the county hub. Sixteen percent of the residents of Broward County are elderly. The unemployment rate in Broward County in 2000 was 5.3%, lower than the state average.
Palm Beach County is the northernmost county in South Florida with a population of almost 1.2 million (Florida Department of Health, 2005h). It is the most affluent county in South Florida with the highest median income. It also has the highest number of residents over 65 years of age. The unemployment rate in 2000 was 5%, lower than the average for the state of Florida.
Monroe County is the southernmost county in South Florida and contains the Florida Keys, with Everglades National Park occupying the vast majority of the county's mainland area. Monroe is the smallest of the four counties with a population of 80,462. In 2000, Monroe County had the second highest median income of the four counties and the lowest unemployment rate of 3.2% (Florida Department of Health, 2005g).
These four counties in South Florida are diverse in geographical size, race and ethnicity, mean age of residents, median income, unemployment rates, and immigration. A comparative examination of the demographic characteristics and the socioeconomic factors traditionally associated with health status and health status indicators in these four counties challenge some long-held stereotypes. Disparities in health status indicators (i.e., birthweight, neonatal and infant death rates, receipt of prenatal care, major causes of death, availability of health care facilities and services, and expenditures for health) have traditionally been associated with minority groups, poor and underserved populations, the very young and the elderly, and groups with limited access to health care facilities (National Center for Health Statistics, 2002). …