The income-associated burden of disease in the United States

In this study, we estimate the total burden of disease associated with income in the US. We calculate the relationships between income and life expectancy, health-adjusted life expectancy, annual years of life lost (YLLs), and health adjusted life years (HALYs).We used the 2000 US Medical Expenditure Panel Survey to derive quality of life estimates by income and age, the 1990–1992 US National Health Interview Survey linked to National Death Index data through the end of 1995 to derive mortality risks by income and by age, and 2000 US mortality data from the National Center for Health Statistics to derive current mortality estimates for the US population by age-group. The bottom 80% of adult income earners’ life expectancy is 4.3 years and 5.8 HALYs shorter relative to those in the top 20% of earnings. This translates into the loss of 11 million YLLs and 17.4 million HALYs each year. Compared with persons living above the poverty threshold, those living below the poverty threshold live an average of 3.2 million fewer HALYs per year—a difference of 8.5 HALYs per individual between age 18 and death. The income-associated burden of disease appears to be a leading cause of morbidity and mortality in the US

Toward a 21st-century health care system: Recommendations for health care reform

The coverage, cost, and quality problems of the U.S. health care system are evident. Sustainable health care reform must go beyond financing expanded access to care to substantially changing the organization and delivery of care. The FRESH-Thinking Project (www.fresh-thinking.org) held a series of workshops during which physicians, health policy experts, health insurance executives, business leaders, hospital administrators, economists, and others who represent diverse perspectives came together. This group agreed that the following 8 recommendations are fundamental to successful reform: 1. Replace the current fee-for-service payment system with a payment system that encourages and rewards innovation in the efficient delivery of quality care. The new payment system should invest in the development of outcome measures to guide payment. 2. Establish a securely funded, independent agency to sponsor and evaluate research on the comparative effectiveness of drugs, devices, and other medical interventions. 3. Simplify and rationalize federal and state laws and regulations to facilitate organizational innovation, support care coordination, and streamline financial and administrative functions. 4. Develop a health information technology infrastructure with national standards of interoperability to promote data exchange. 5. Create a national health database with the participation of all payers, delivery systems, and others who own health care data. Agree on methods to make de-identified information from this database on clinical interventions, patient outcomes, and costs available to researchers. 6. Identify revenue sources, including a cap on the tax exclusion of employer-based health insurance, to subsidize health care coverage with the goal of insuring all Americans. 7. Create state or regional insurance exchanges to pool risk, so that Americans without access to employer-based or other group insurance could obtain a standard benefits package through these exchanges. Employers should also be allowed to participate in these exchanges for their employees' coverage. 8. Create a health coverage board with broad stakeholder representation to determine and periodically update the affordable standard benefit package available through state or regional insurance exchanges

Sociodemographics, self-rated health, and mortality in the US

Using data from the 1987 National Medical Expenditure Survey, a representative sample of US civilians, and their 5-year mortality, we examined the adjusted relationships among baseline self-reported health, derived from SF-20 subscales (health perceptions, physical function, role function and mental health) and sociodemographics (age, sex, race/ethnicity, income and education) and subsequent mortality. Included were 21,363 persons aged 21 and over, with complete follow-up on 19,812. Physical function showed the greatest decline with age, whereas mental health increased slightly. Women reported lower health for all scales except role function. Greater income was associated with better health, least marked for mental health. Greater education was associated with better health, most marked for health perceptions. Compared with whites, blacks reported lower health, whereas Latinos reported higher health. Lower self-reported health predicted increased adjusted mortality. After adjustment for baseline self-rated health, the relationships between income and education and mortality were greatly attenuated, whereas the relationships between age, gender, race/ethnicity and mortality were not. Self-rated health exhibited more profound relationships with mortality in younger persons, those with more education, and whites. In conclusion, lower socioeconomic status (SES), and being black are associated with lower reported health status and higher mortality; women report lower health status but exhibit lower mortality; and Latinos report higher health status and exhibit lower mortality. The effects of SES on mortality are largely explained by their associations with self-rated health, whereas, the effects of gender and race/ethnicity on mortality appear to act through independent pathways. Because of these differential sociodemographic relationships caution is urged when using self-rated health measures in research, clinical, and policy settings.Self-reported health Sociodemographic factors Mortality USA

The income-associated burden of disease in the United States

In this study, we estimate the total burden of disease associated with income in the US. We calculate the relationships between income and life expectancy, health-adjusted life expectancy, annual years of life lost (YLLs), and health adjusted life years (HALYs).We used the 2000 US Medical Expenditure Panel Survey to derive quality of life estimates by income and age, the 1990-1992 US National Health Interview Survey linked to National Death Index data through the end of 1995 to derive mortality risks by income and by age, and 2000 US mortality data from the National Center for Health Statistics to derive current mortality estimates for the US population by age-group. The bottom 80% of adult income earners' life expectancy is 4.3 years and 5.8 HALYs shorter relative to those in the top 20% of earnings. This translates into the loss of 11 million YLLs and 17.4 million HALYs each year. Compared with persons living above the poverty threshold, those living below the poverty threshold live an average of 3.2 million fewer HALYs per year--a difference of 8.5 HALYs per individual between age 18 and death. The income-associated burden of disease appears to be a leading cause of morbidity and mortality in the US.US Health inequalities Poverty Burden of disease analysis

Methodological concerns and recommendations on policy consequences of the World Health Report 2000

Made available in DSpace on 2010-08-23T16:58:46Z (GMT). No. of bitstreams: 3 license.txt: 1848 bytes, checksum: c064432b9f18503059d3b17e7ea11c3b (MD5) LANDMANN_TRAVASSOS_VIACAVA_Methodological Concerns_2001.pdf: 92641 bytes, checksum: ad7c4e07ccd213de362e3cfbf38fc8aa (MD5) LANDMANN_TRAVASSOS_VIACAVA_Methodological Concerns_2001.pdf.txt: 39800 bytes, checksum: b87e36dfd3146e66ad3a491299b38c6e (MD5) Previous issue date: 2001-05Made available in DSpace on 2010-11-04T14:19:57Z (GMT). No. of bitstreams: 3 LANDMANN_TRAVASSOS_VIACAVA_Methodological Concerns_2001.pdf.txt: 39800 bytes, checksum: b87e36dfd3146e66ad3a491299b38c6e (MD5) LANDMANN_TRAVASSOS_VIACAVA_Methodological Concerns_2001.pdf: 92641 bytes, checksum: ad7c4e07ccd213de362e3cfbf38fc8aa (MD5) license.txt: 1848 bytes, checksum: c064432b9f18503059d3b17e7ea11c3b (MD5) Previous issue date: 2001-05Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.University of California. Department of Family and Community Medicine. San Francisco, USA.City University of New York Medical School. Department of Community Health and Social Medicine. New York, USA.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnologia em Saúde. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Consultant to Ministry of Health. Montevideo, Uruguay.Canadian Institute for Health Information. Ottawa, Canada.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Department of Economics. Universitat Pompeu Fabra. Barcelona, Spain.Health Unit. Institute of Development Studies, Sussex, UK.Johns Hopkins Medical Institutions. Baltimore, USA.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnologia em Saúde. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnologia em Saúde. Rio de Janeiro, RJ, Brasil

Overcoming Depression on the Internet (ODIN) (2): A Randomized Trial of a Self-Help Depression Skills Program With Reminders

BACKGROUND: Guided self-help programs for depression (with associated therapist contact) have been successfully delivered over the Internet. However, previous trials of pure self-help Internet programs for depression (without therapist contact), including an earlier trial conducted by us, have failed to yield positive results. We hypothesized that methods to increase participant usage of the intervention, such as postcard or telephone reminders, might result in significant effects on depression. OBJECTIVES: This paper presents a second randomized trial of a pure self-help Internet site, ODIN (Overcoming Depression on the InterNet), for adults with self-reported depression. We hypothesized that frequently reminded participants receiving the Internet program would report greater reduction in depression symptoms and greater improvements in mental and physical health functioning than a comparison group with usual treatment and no access to ODIN. METHODS: This was a three-arm randomized control trial with a usual treatment control group and two ODIN intervention groups receiving reminders through postcards or brief telephone calls. The setting was a nonprofit health maintenance organization (HMO). We mailed recruitment brochures by US post to two groups: adults (n = 6030) who received depression medication or psychotherapy in the previous 30 days, and an age- and gender-matched group of adults (n = 6021) who did not receive such services. At enrollment and at 5-, 10- and 16-weeks follow-up, participants were reminded by email (and telephone, if nonresponsive) to complete online versions of the Center for Epidemiological Studies Depression Scale (CES-D) and the Short Form 12 (SF-12). We also recorded participant HMO health care services utilization in the 12 months following study enrollment. RESULTS: Out of a recruitment pool of 12051 approached subjects, 255 persons accessed the Internet enrollment site, completed the online consent form, and were randomized to one of the three groups: (1) treatment as usual control group without access to the ODIN website (n = 100), (2) ODIN program group with postcard reminders (n = 75), and (3) ODIN program group with telephone reminders (n = 80). Across all groups, follow-up completion rates were 64% (n = 164) at 5 weeks, 68% (n = 173) at 10 weeks, and 66% (n = 169) at 16 weeks. In an intention-to-treat analysis, intervention participants reported greater reductions in depression compared to the control group (P = .03; effect size = 0.277 standard deviation units). A more pronounced effect was detected among participants who were more severely depressed at baseline (P = .02; effect size = 0.537 standard deviation units). By the end of the study, 20% more intervention participants moved from the disordered to normal range on the CES-D. We found no difference between the two intervention groups with different reminders in outcomes measures or in frequency of log-ons. We also found no significant intervention effects on the SF-12 or health care services. CONCLUSIONS: In contrast to our earlier trial, in which participants were not reminded to use ODIN, in this trial we found a positive effect of the ODIN intervention compared to the control group. Future studies should address limitations of this trial, including relatively low enrollment and follow-up completion rates, and a restricted number of outcome measures. However, the low incremental costs of delivering this Internet program makes it feasible to offer this type of program to large populations with widespread Internet access