173854
Impact of the Aging Baby Boomers In San Mateo County
Crispin Delgado, MPP
,
Health Policy and Planning, San Mateo County Health Department, San Mateo, CA
Swati Deshpande, PhD
,
Disease Control and Prevention, San Mateo County Health System, San Mateo, CA
Daniel Brown, MPH
,
Public Health Department, San Mateo County Health Department, San Mateo, CA
Scott Morrow, MD, MPH
,
Health Officer, San Mateo County Health System, San Mateo, CA
The San Mateo County Health Department, California, in collaboration with local leaders in housing, transportation, and health developed an adaptable computer-based model that projects the socio-demographic characteristics of the population for the years 2020 and 2030. Although many studies have predicted significant demographic shifts with the aging of the baby boomers, little was known about the impact at the local level. The model was based on Public Use Micro-Samples (PUMS) census data, coupled with local quantitative and qualitative data. Local data methods included a targeted population survey that oversampled vulnerable populations, such as African-Americans, Latinos, Asian/Pacific Islander (PI), and low-incomes individuals. Focus groups were also held with monolingual Cantonese and Mandarin speakers. Efforts were made to capture the behavior of these populations, as future plans may be differ across populations, thereby impacting the level and types of services offered by the County. Preliminary findings show that Latino and Asian/PI older adult populations will increase by 170% over the next 25 years. Surprisingly, the study found that income was a better indicator of longevity in the County vis-à-vis home ownership status. Also, older adults with incomes below 400% of the Federal Poverty Level (FPL) were more than twice as likely than those above 400% FPL to die or leave the County in the next 25 years. This model, and the rich data it provides, will undoubtedly help County departments, city governments, and the community plan for the aging of the Baby Boomers, and its implications on demand for limited community resources.
Learning Objectives: 1. List research methods used to create a locally specific aging projection model to the year 2030
2. Describe approaches for cross-sectoral collaboration and the role of a diverse community voice in the planning process
3. Discuss potential uses of data by government and the local community
Keywords: Aging, Access and Services
Presenting author's disclosure statement:Qualified on the content I am responsible for because: I was the project manager overseeing the development and implementation of the Aging 2020 model for San Mateo County. I worked closely with contractors over 14 months to ensure the model development was aligned with the scope of work, also played an integral part in the local data collection, including the supplemental survey, monolingual focus groups, and local primary data sources. I have spent the last six months interpreting baseline data into key findings.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.
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