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Vital Signs: Transit Cost-Effectiveness – by operator
data.bayareametro.gov | Last Updated 2018-07-06T18:04:51.000ZVITAL SIGNS INDICATOR Transit Cost-Effectiveness (T13) FULL MEASURE NAME Net cost per transit boarding (cost per boarding minus fare per boarding) LAST UPDATED May 2017 DESCRIPTION Transit cost-effectiveness refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. DATA SOURCE Federal Transit Administration: National Transit Database http://www.ntdprogram.gov/ntdprogram/data.htm Bureau of Labor Statistics: Consumer Price Index http://www.bls.gov/data/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data. Financial data was inflation-adjusted to match 2015 dollar values using metro-specific Consumer Price Indices.
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Vital Signs: Rent Payments – by metro
data.bayareametro.gov | Last Updated 2019-10-25T20:17:20.000ZVITAL SIGNS INDICATOR Rent Payments (EC8) FULL MEASURE NAME Median rent payment LAST UPDATED August 2019 DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time. DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a U.S. Census Bureau: American Community Survey 2005-2017 http://api.census.gov Note: Form B25058; 1-YR Bureau of Labor Statistics: Consumer Price Index 1970-2017 http://www.bls.gov/data/ Note: All Urban Consumers Data Table (by metro) CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries. Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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Vital Signs: Transit Cost-Effectiveness – by metro
data.bayareametro.gov | Last Updated 2018-07-06T18:04:53.000ZVITAL SIGNS INDICATOR Transit Cost-Effectiveness (T13) FULL MEASURE NAME Net cost per transit boarding (cost per boarding minus fare per boarding) LAST UPDATED May 2017 DESCRIPTION Transit cost-effectiveness refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. DATA SOURCE Federal Transit Administration: National Transit Database http://www.ntdprogram.gov/ntdprogram/data.htm Bureau of Labor Statistics: Consumer Price Index http://www.bls.gov/data/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data. Financial data was inflation-adjusted to match 2015 dollar values using metro-specific Consumer Price Indices.
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Vital Signs: Rent Payments – Bay Area
data.bayareametro.gov | Last Updated 2019-10-25T20:17:35.000ZVITAL SIGNS INDICATOR Rent Payments (EC8) FULL MEASURE NAME Median rent payment LAST UPDATED September 2016 DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time. DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a U.S. Census Bureau: American Community Survey 2005-2015 http://api.census.gov Note: Form B25058; 1-YR Bureau of Labor Statistics: Consumer Price Index 1970-2015 http://data.bls.gov Note: All Urban Consumers Data Table (by metro) CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries. Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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Vital Signs: Transit Cost-Effectiveness – Bay Area
data.bayareametro.gov | Last Updated 2018-07-06T18:04:54.000ZVITAL SIGNS INDICATOR Transit Cost-Effectiveness (T13) FULL MEASURE NAME Net cost per transit boarding (cost per boarding minus fare per boarding) LAST UPDATED May 2017 DESCRIPTION Transit cost-effectiveness refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. DATA SOURCE Federal Transit Administration: National Transit Database http://www.ntdprogram.gov/ntdprogram/data.htm Bureau of Labor Statistics: Consumer Price Index http://www.bls.gov/data/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data. Financial data was inflation-adjusted to match 2015 dollar values using metro-specific Consumer Price Indices.
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Vital Signs: Transit Cost-Effectiveness – by Mode
data.bayareametro.gov | Last Updated 2018-07-06T18:04:45.000ZVITAL SIGNS INDICATOR Transit Cost-Effectiveness (T13) FULL MEASURE NAME Net cost per transit boarding (cost per boarding minus fare per boarding) LAST UPDATED May 2017 DESCRIPTION Transit cost-effectiveness refers to both the total and net costs per transit boarding, both of which are adjusted to reflect inflation over time. Net costs reflect total operating costs minus farebox revenue (i.e. operating costs that are not directly funded by system users). The dataset includes metropolitan area, regional, mode, and system tables for net cost per boarding, total cost per boarding, and farebox recovery ratio. DATA SOURCE Federal Transit Administration: National Transit Database http://www.ntdprogram.gov/ntdprogram/data.htm Bureau of Labor Statistics: Consumer Price Index http://www.bls.gov/data/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) Simple modes were aggregated to combine the various bus modes (e.g. rapid bus, express bus, local bus) into a single mode to avoid incorrect conclusions resulting from mode recoding over the lifespan of NTD. For other metro areas, operators were identified by developing a list of all urbanized areas within a current MSA boundary and then using that UZA list to flag relevant operators; this means that all operators (both large and small) were included in the metro comparison data. Financial data was inflation-adjusted to match 2015 dollar values using metro-specific Consumer Price Indices.
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Vital Signs: Rent Payments – by county
data.bayareametro.gov | Last Updated 2019-10-25T20:18:35.000ZVITAL SIGNS INDICATOR Rent Payments (EC8) FULL MEASURE NAME Median rent payment LAST UPDATED August 2019 DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time. DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a U.S. Census Bureau: American Community Survey 2005-2017 http://api.census.gov Note: Form B25058; 1-YR Bureau of Labor Statistics: Consumer Price Index 1970-2017 http://www.bls.gov/data/ Note: All Urban Consumers Data Table (by metro) CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries. Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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Vital Signs: Rent Payments – by city
data.bayareametro.gov | Last Updated 2019-10-25T20:17:50.000ZVITAL SIGNS INDICATOR Rent Payments (EC8) FULL MEASURE NAME Median rent payment LAST UPDATED August 2019 DESCRIPTION Rent payments refer to the cost of leasing an apartment or home and serves as a measure of housing costs for individuals who do not own a home. The data reflect the median monthly rent paid by Bay Area households across apartments and homes of various sizes and various levels of quality. This differs from advertised rents for available apartments, which usually are higher. Note that rent can be presented using nominal or real (inflation-adjusted) dollar values; data are presented inflation-adjusted to reflect changes in household purchasing power over time. DATA SOURCE U.S. Census Bureau: Decennial Census 1970-2000 https://nhgis.org Note: Count 1 and Count 2; Form STF1; Form SF3a U.S. Census Bureau: American Community Survey 2005-2017 http://api.census.gov Note: Form B25058; 1-YR Bureau of Labor Statistics: Consumer Price Index 1970-2017 http://www.bls.gov/data/ Note: All Urban Consumers Data Table (by metro) CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Rent data reflects median rent payments rather than list rents (refer to measure definition above). Larger geographies (metro and county) rely upon ACS 1-year data, while smaller geographies rely upon ACS 5-year rolling average data. 1970 Census data for median rent payments has been imputed by ABAG staff as the source data only provided the mean, rather than the median, monthly rent. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries. Inflation-adjusted data are presented to illustrate how rent payments have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself.
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Vital Signs: Life Expectancy – by ZIP Code
data.bayareametro.gov | Last Updated 2018-07-06T18:05:06.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION 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. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link 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 CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) 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 im
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Vital Signs: Life Expectancy – Bay Area
data.bayareametro.gov | Last Updated 2018-07-06T18:05:05.000ZVITAL SIGNS INDICATOR Life Expectancy (EQ6) FULL MEASURE NAME Life Expectancy LAST UPDATED April 2017 DESCRIPTION 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. DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link 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/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) 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. 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 https://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). 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. In this way, the original 305 Bay Area Zip codes were reduced to 218 Zip