Life Expectancy | Vital Signs

How healthy is the Bay Area’s population?

Life Expectancy

Definition:

Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

Life expectancy gives a snapshot of a population’s health status and health outcomes. Like life expectancy trends nationwide, life expectancy across the region’s population has seen long-term improvement largely due to advancements in medical care. At the local level, differences in life expectancy can indicate health inequities between neighborhoods. Analyzing localities in the Bay Area that have relatively higher and lower life expectancies can help clarify the factors that contribute to long and healthy lives.

San Mateo County has the highest life expectancy in the region at 83.7 years

79.6

Life expectancy in Solano County was 79.6 years, lowest among Bay Area counties

10.4

Life expectancy in San Francisco improved 10.4 years from 1990 to 2013, largely due to better treatment and prevention of HIV/AIDS

73.4

ZIP Code 94103, representing SOMA in San Francisco, had the lowest life expectancy in the region at 73.4 years

The difference between highest and lowest life expectancy for Bay Area ZIP Codes was over 13 years

Regional Performance

Life expectancy in the region has increased, indicating the Bay Area’s population is getting healthier.

Life expectancy in the Bay Area was over 82 years as of 2013, a six year improvement compared to 1990. Regional life expectancy increased almost every year on record since 1990. The most recent year to see a drop was 2005, around the time of a particularly severe flu season. Prior to that, life expectancy dipped in 1993 around the height the AIDS epidemic. Significant healthcare improvements for people living with HIV in the late 1990s had a substantial impact on health outcomes, particularly in San Francisco County where life expectancy jumped nearly six years between 1990 and 2000.

While San Francisco County saw exceptional improvement in life expectancy after 1990, the other eight Bay Area counties also saw life expectancy increases. There are, however, widening disparities between counties as life expectancy is increasing more slowly in Solano compared to the rest of the region in recent years. In 2000, the gap in life expectancy between Solano County and the regional average was 1.5 years. By 2013, that number had grown to 3.8 years.

Historical Trend for Life Expectancy

Local Focus

Life expectancies across different Bay Area ZIP Codes varied by as much as 13 years.

Life expectancy within different Bay Area ZIP Codes ranged from a low of 73 years to a high of 86 years. Life expectancy in ZIP Codes representing neighborhoods in the Berkeley Hills in the East Bay and around Los Altos Hills in the South Bay have some of the best health outcomes in the region. Meanwhile, ZIP Codes in Santa Rosa in Sonoma County, urban neighborhoods areas in Solano County, and Bayside neighborhoods in the East Bay have relatively lower life expectancies.

The lowest life expectancies in the region were in the Downtown and Tenderloin areas of San Francisco. Life expectancies in neighboring Eureka Valley were 10 years higher. Similarly, life expectancy in East Oakland is 75 years compared to 85 years in the Oakland Hills. San Francisco and Oakland exemplify some of the significant health inequities that exist in the Bay Area.

Life Expectancy by ZIP Code

2000 2013

Click on a shape on the map for more information.

Sources:

State of California, Department of Health: Death Records (1990-2013)

California Department of Finance: Population Estimates

Annual Intercensal Population Estimates (1990-2010)

Table P-2: County Population by Age (2010-2013)

http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census

ZCTA Population (2000-2010)

http://factfinder.census.gov

U.S. Census Bureau: American Community Survey

5-Year Population Estimates (2013)

http://factfinder.census.gov

Image: iStockPhoto (#618069482)

Methodology Notes:

Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.