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2010
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9 pages
1 file
AI-generated Abstract
The paper analyzes the prevalence of uninsurance in the District of Columbia using data from the 2009 DC Health Insurance Survey, which included interviews from over 4,700 households. Key findings highlight the demographic characteristics of the uninsured, their reasons for lacking insurance, and systemic issues, such as income levels and employment status, contributing to uninsurance. It aims to inform policy solutions to address health coverage gaps.
Ucla Center For Health Policy Research, 2000
The Journal of Rural Health, 2006
Rural policy brief, 2013
Key Findings. (1) A larger proportion of the rural population than the urban population is uninsured and low income (living at or below 138% of the federal poverty line [FPL]) (9.9% as compared to 8.5%) and a larger proportion of the rural population than the urban population will be eligible for subsidized Health Insurance Marketplace (HIM) coverage due to income levels and current lack of insurance (10.7% as compared to 9.6%). (2) Assuming full Medicaid expansion, a larger proportion of the rural uninsured than the urban uninsured would be eligible for Medicaid (43.5% as compared to 38.5%). (3) A smaller proportion of the rural uninsured than the urban uninsured has income above 400% FPL and thus will not qualify for either Medicaid or HIM subsidies (10% as compared to 14.1%). (4) The proportion of the uninsured population potentially eligible for Medicaid expansion is highest in the rural South (47.5%) and lowest in the urban Northeast (32.5%) and the rural Northeast (35.8%).
2002
An estimated 14.0% of the U.S. population lacked health insurance coverage in 2000, down from 14.3% in 1999. When examined by state, estimates of the percent uninsured ranged from a low of 5.9% in Rhode Island to a high of 23.8% in New Mexico. Generally, states in the Midwest and New England have lower rates of uninsured, while states in the Southwestern portion of the nation have higher shares of their populations without coverage. These state-level estimates are based on the March 2001 Current Population Survey (CPS), and must be interpreted with caution because they are based on survey samples. When sampling variation is taken into account, to allow one to say with 90% reliability that the percent uninsured in the state lies between specified low and high estimates, the uninsured rate in 14 states and the District of Columbia is not different statistically from the uninsured rate nationwide. The uninsured rate is statistically lower than the national rate in 24 states, and statistically higher in the remaining 12 states. State-level analysis is only one way to examine data about health insurance coverage. Some factors related to the percent of a state's population that is uninsured may be affected by the state, such as eligibility criteria for the state's Medicaid and State Children's Health Insurance programs or other programs for those lacking health insurance. Other factors may be beyond the state's direct control, such as the willingness of employers to offer coverage and the financial resources of the state's population to purchase coverage. This report will be updated annually, when new data become available. For related information,
2002
An estimated 14.0% of the U.S. population lacked health insurance coverage in 2000, down from 14.3% in 1999. When examined by state, estimates of the percent uninsured ranged from a low of 5.9% in Rhode Island to a high of 23.8% in New Mexico. Generally, states in the Midwest and New England have lower rates of uninsured, while states in the Southwestern portion of the nation have higher shares of their populations without coverage. These state-level estimates are based on the March 2001 Current Population Survey (CPS), and must be interpreted with caution because they are based on survey samples. When sampling variation is taken into account, to allow one to say with 90% reliability that the percent uninsured in the state lies between specified low and high estimates, the uninsured rate in 14 states and the District of Columbia is not different statistically from the uninsured rate nationwide. The uninsured rate is statistically lower than the national rate in 24 states, and statistically higher in the remaining 12 states. State-level analysis is only one way to examine data about health insurance coverage. Some factors related to the percent of a state's population that is uninsured may be affected by the state, such as eligibility criteria for the state's Medicaid and State Children's Health Insurance programs or other programs for those lacking health insurance. Other factors may be beyond the state's direct control, such as the willingness of employers to offer coverage and the financial resources of the state's population to purchase coverage. This report will be updated annually, when new data become available. For related information,
Public health reports (Washington, D.C. : 1974)
Lack of health insurance coverage for working-age adults is one of the most pressing issues facing the U.S. population, and it continues to be a concern for a large number of people. In the absence of a national solution, the states and municipalities are left to address this need. We examined the disparities in uninsurance prevalence by state and metropolitan areas in the U.S. and among racial/ethnic groups. Data from the 2006 Behavioral Risk Factor Surveillance System (BRFSS) were analyzed for working-age adults 18 to 64 years of age. In 2006, according to the BRFSS data, overall 18.6% (standard error = 0.20) of working-age adults were without health insurance coverage; by state, this proportion ranged from 9.7% to 29.0%. Health insurance coverage varied by state and metropolitan area and racial/ethnic group, and a higher age-adjusted prevalence of uninsurance was observed for non-Hispanic black and Hispanic respondents. A substantial proportion of working-age Americans remain wit...
Journal of Adolescent Health, 2004
To identify sociodemographic factors associated with being uninsured among young adults in a state sample (Massachusetts) and to examine the independent association of insurance status with the young adult's reporting no health maintenance visit (check-up) in the past 2 years or reporting an inability to afford needed health care in the last 12 months. Methods: Secondary analysis of data from the Massachusetts Behavioral Risk Factor Surveillance System for the years 1998-2000. In this cross-sectional study, data were examined for 1673 19-to 24-years-olds who provided information on sociodemographic variables, health insurance status, perceived inability to afford care, and health care use. Multiple logistic regression was used to estimate the odds of being uninsured. Subsequently, multiple logistic regression was used to estimate the odds of having no checkup in the last 2 years and of reporting the inability to afford needed health care in the last year. Results: 15% of young adults were uninsured, including 20% of males and 10% of females. For both genders, the adjusted odds of being uninsured were lower for students and higher for those with a household income between $15,000 and $24,999. Uninsured young men, but not women, had significantly higher odds of not having a routine checkup in the last 2 years. Uninsured young adults of both genders had significantly higher odds of reporting the inability to afford needed care in the past 12 months. Conclusions: Programs and policies that seek to reduce the rates of uninsured young adults should especially target males and nonstudents. Improving health insurance coverage, especially for young adult males, may be associated with improved preventive health care access.
2002
This report describes the general population of the uninsured and the insured, whether insured through a private, public, or state option. The data included in this report covers several different categories of the uninsured in Texas: by age, race, income, employment status, educational attainment, citizenship status, and type of family. A plethora of resources are available that measure different demographic information on those that are insured and uninsured. A summary of these different data sources along with their general findings and limitations is also provided.
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