Bryan Tysinger
Dados Biográficos
| ID | 5546034 |
|---|---|
| NOME | Bryan Tysinger |
| PRENOMES | Bryan |
| SOBRENOME | Tysinger |
| ASSINATURA | TYSINGER B |
| AFILIAÇÕES | University of Southern California |
| ORCID | 0000-0002-8497-3664 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 4 |
| TOTAL DE CITAÇÕES | 7 |
| TOTAL COMO AUTOR | 4 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2017 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2025 |
| ÍNDICE H | 1 |
The urban–rural gap in older Americans’ healthy life expectancy
PURPOSE: Estimate health-quality-adjusted life expectancy (QALE) for Americans nearing retirement age and assess rural-urban disparities in QALE. METHODS: We used a dynamic microsimulation model based on Health and Retirement Study data to estimate the quantity and health quality of expected future life years for rural and urban Americans ages 59-60 in 2014-2020. FINDINGS: Cohort life expectancy at age 60 (LE) for urban and rural men was 22.9 and…
Long-Term Health Improvements and Economic Performance Among Individuals With Diabetes
This cross-sectional study demonstrated that while people with diabetes experienced meaningful health improvements, they saw little progress in economic performance. Changing patient selection appears to play a role. Future research is needed to disentangle the paradox
The Impact of Changes in Population Health and Mortality on Future Prevalence of Alzheimer’s Disease and Other Dementias in the United States
We assessed potential benefits for older Americans of reducing risk factors associated with dementia. A dynamic simulation model tracked a national cohort of persons 51 and 52 years of age to project dementia onset and mortality in risk reduction scenarios for diabetes, hypertension, and dementia. We found reducing incidence of diabetes by 50% did not reduce number of years a person ages 51 or 52 lived with dementia and increased the population a…
Using Self-reports or Claims to Assess Disease Prevalence
BACKGROUND: Two common ways of measuring disease prevalence include: (1) using self-reported disease diagnosis from survey responses; and (2) using disease-specific diagnosis codes found in administrative data. Because they do not suffer from self-report biases, claims are often assumed to be more objective. However, it is not clear that claims always produce better prevalence estimates. OBJECTIVE: Conduct an assessment of discrepancies between s…
The Impact of Changes in Population Health and Mortality on Future Prevalence of Alzheimer’s Disease and Other Dementias in the United States
We assessed potential benefits for older Americans of reducing risk factors associated with dementia. A dynamic simulation model tracked a national cohort of persons 51 and 52 years of age to project dementia onset and mortality in risk reduction scenarios for diabetes, hypertension, and dementia. We found reducing incidence of diabetes by 50% did not reduce number of years a person ages 51 or 52 lived with dementia and increased the population a…
The Impact of Changes in Population Health and Mortality on Future Prevalence of Alzheimer’s Disease and Other Dementias in the United States
We assessed potential benefits for older Americans of reducing risk factors associated with dementia. A dynamic simulation model tracked a national cohort of persons 51 and 52 years of age to project dementia onset and mortality in risk reduction scenarios for diabetes, hypertension, and dementia. We found reducing incidence of diabetes by 50% did not reduce number of years a person ages 51 or 52 lived with dementia and increased the population a…
Using Self-reports or Claims to Assess Disease Prevalence
BACKGROUND: Two common ways of measuring disease prevalence include: (1) using self-reported disease diagnosis from survey responses; and (2) using disease-specific diagnosis codes found in administrative data. Because they do not suffer from self-report biases, claims are often assumed to be more objective. However, it is not clear that claims always produce better prevalence estimates. OBJECTIVE: Conduct an assessment of discrepancies between s…
The urban–rural gap in older Americans’ healthy life expectancy
PURPOSE: Estimate health-quality-adjusted life expectancy (QALE) for Americans nearing retirement age and assess rural-urban disparities in QALE. METHODS: We used a dynamic microsimulation model based on Health and Retirement Study data to estimate the quantity and health quality of expected future life years for rural and urban Americans ages 59-60 in 2014-2020. FINDINGS: Cohort life expectancy at age 60 (LE) for urban and rural men was 22.9 and…
Long-Term Health Improvements and Economic Performance Among Individuals With Diabetes
This cross-sectional study demonstrated that while people with diabetes experienced meaningful health improvements, they saw little progress in economic performance. Changing patient selection appears to play a role. Future research is needed to disentangle the paradox
Environmental health (4 obras) · Gerontology (4 obras) · Medicine (4 obras) · Population (4 obras) · Chronic Disease Management Strategies (2 obras) · Demography (2 obras) · Demography (2 obras) · Disease (2 obras) · Health disparities and outcomes (2 obras) · Sociology (2 obras)