neighborhood profile methodology 082914 final for web profiles... · santa clara county city and...

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Methodology

SantaClaraCountyCityandSmallArea/NeighborhoodProfilesThe goal of the Santa Clara County City and Small Area/Neighborhood Profiles is to improve access to data at the sub‐county geographic level that local agencies and organizations can use for planning interventions and influencing policy. Using city and small area/neighborhood level data can help to understand how where we live, work, and play impacts health and well‐being. The profiles provide a snapshot of conditions that influence health as well as indicators of health status in Santa Clara County cities and small areas/neighborhoods. This document provides an overview of the methods used to define small areas/neighborhoods and select indicators, as well as the data sources used for the profiles.

Definingsmallarea/neighborhoodboundariesandnamesSmall area/neighborhood boundaries and names were defined in consultation with the Santa Clara County Planning Office, Department of Planning and Development, with feedback from city planning departments. City planners could send the boundaries out for broader review to other agencies and organizations at their own discretion. The small area/neighborhood boundaries were defined based on the following guidelines, which were designed to better enable SCCPHD to report statistics where the number of cases or events are small and to make updates more feasible:

• Each small area/neighborhood should have a minimum of 10,000 residents • Each small area/neighborhood should consist of a minimum of 2 to 3 census tracts • Census tracts should not be split across small areas/neighborhoods • Small areas/neighborhoods should be reasonably within or correlate with city limits • Each city should have a minimum of two small areas/neighborhoods

In addition, small area/neighborhood names and boundaries were defined to be as consistent as possible with pre‐existing neighborhoods. In order to adhere to the criteria above, however, it was not always possible to align boundaries or select small area/neighborhood names that were identical to existing boundaries. In some cases, small areas contain multiple pre‐existing neighborhoods and in other cases large pre‐existing neighborhoods were split into two or more small areas. In either case, neighborhood names were incorporated into the name of the small area in which they are contained, where known.

One hundred and nine (109) small areas/neighborhoods were defined from the county’s 372 census tracts. Every census tract in Santa Clara County is now assigned to a small area/neighborhood. Please contact [email protected] with any questions on small area/neighborhood boundaries.

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IndicatorselectionprocessThe City and Small Area/Neighborhood Profile project utilizes a health equity framework, similar to that employed by the California Department of Public Health’s Healthy Communities Data and Indictors (HCI) project. For more information on the Healthy Communities framework, please see: http://www.cdph.ca.gov/programs/Pages/HealthyCommunityIndicators.aspx. The Santa Clara County Public Health Department (SCCPHD) identified indicators within the broad domains of demographics, economic and educational opportunities, healthy and safe environment, and health status. In order to make the profiles useable, in terms of length, and feasible to update on a regular basis, SCCPHD developed criteria to guide the selection of potential indicators. Indicators were selected after reviewing similar projects from other jurisdictions. Criteria included:

Relevant to programmatic and policy‐related activities underway in agencies and organizations in the county In current use by other large local health departments or the CDPH HCI project Data on the indicator available at the census tract level Data available on a regular basis (at least annually) by the agency or organization providing data on the indicator

The final list of indicators was defined and selected by SCCPHD, based on feedback from county and city planning departments and other stakeholders. The profiles include data on the following topics:

Demographic information including the total population, age, gender, and race/ethnicity of small area/neighborhood residents Social determinants of health, including socioeconomic factors, education, and the built and social environment Health outcomes, including life expectancy, mortality and causes of death, communicable and infectious disease, and maternal and

child health

Please contact [email protected] with questions on city and small area/neighborhood indicators.

DataSourcesSCCPHD utilized data from local, regional, state, and national surveys, databases, and registries. The table below describes each data source and where to find more information if available.

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DemographicSnapshotIndicator Significance to public health How the measure was

calculated Data source

Population size Population size provides information about the number of people living in the county, city, or neighborhood, which can be used to address issues such as where services like clinics and hospitals should be located.

Count of population U.S. Census Bureau, 2010 U.S. Census Cities: DP‐1 Neighborhoods: P1

Race/ethnicity Race/ethnicity is important for understanding the composition of the county and comparing diversity of cities or neighborhoods. Health status and life expectancy varies by racial/ethnic group, so understanding the racial/ethnic composition of an area can help to target programs and policies to meet the needs of residents.1

Percentage of population in four racial/ethnic groups (African American, Asian/Pacific Islander, Latino, and non‐Hispanic White)

U.S. Census Bureau, 2010 U.S. Census Cities: DP‐1 Neighborhoods: P5

Foreign‐born Foreign‐born residents often have different health, social, and economic concerns than those born in the U.S. Immigrants are less likely to be insured but may be healthier than U.S. born residents.2 Understanding the proportion of residents who are foreign‐born in an area can help to determine community needs

Percentage of population born outside the U.S.

U.S. Census Bureau, American Community Survey 5‐Year Estimates Cities: 2006‐2010 (DP02) Neighborhoods: 2007‐2011 (B05012)

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and plan for services.

Speaks a language other than English at home

Areas with high percentages of residents who speak a language other than English at home can be helpful for locating interventions and healthcare services to benefit immigrant residents and families.

Percentage of population who speak a language at home other than English


Single parent households Single parent households are households that include children who reside with only one parent. Studies have shown that children raised by single mothers have poorer physical and mental health than children raised in a household with two biological parents.3 Information on the percentage of single parent households for cities and neighborhoods can help to target services to provide more support for single parents and support maternal and child health.

Percentage of population who are either male householder, no wife present with own children under 18 years or female householder, no husband present with own children under 18 years Excludes single parents living with unmarried partners. Same‐sex couples are counted as either married or as an unmarried couple living together depending on their marital status.


Households with children Because many public health programs are designed for early intervention and prevention, identifying areas in the county with a higher proportion of

Percentage of households with children

U.S. Census Bureau, 2010 U.S. Census Cities: DP‐1

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households with children can help allocate resources to for child health and prevention.

Neighborhoods: P20

Average household size Average household size is an indication of the number of people residing in a household. Households with many members may experience higher rates of overcrowding, which has been found to affect health and social outcomes.4 Differences in average household size in cities and neighborhoods can also be an indicator of family size and composition, such as a higher proportion of households where people are living alone.

Sum of number of people living in occupied households, divided by the number of occupied households in a small area/neighborhood or city


Age groups

Understanding the age breakdown in an area can help to target services and allocate resources. For example, a community with a larger proportion of older adults may need services that support “aging in place” and independent living, chronic disease management, and social connections.

Percentage of population ages 0‐5, 6‐11, 12‐17, 18‐24, 25‐34, 35‐44, 45‐54, 55‐64, and 65 and older

U.S. Census Bureau, 2010 U.S. Census Cities: QTP1 Neighborhoods: P12

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EconomicandEducationalOpportunitiesIndicator Significance to public health How the measure was


Unemployed (ages >16 years) Unemployment can be a significant source of stress, often leading to lower socioeconomic status, loss of social connections, reduced wealth, and other outcomes which contribute to poor health.5 People who are unemployed are at increased risk for poor mental and physical health and engaging in risky health behaviors.6 Research suggests that people who have lost their jobs are more likely to develop adverse health conditions such as heart disease.7 Identifying areas in the county with a higher unemployment rate can help allocate resources for job training and placement.

Percentage of population ages 16 and older in the civilian labor force who are presently unemployed

Neighborhoods: U.S. Census Bureau, American Community Survey 2007‐2011 5‐Year Estimates (B23025) Cities: State of California Employment Development Department, November 2012

Median household income Higher income is associated with better health care access and outcomes and longer life expectancy.8 The County of Santa Clara has one of the highest median household incomes in the country. However, there is a wide range of median household income

Median household income in the past 12 months (in 2011 inflation‐adjusted dollars) For small areas/neighborhoods, household income was available in defined income ranges only (e.g., $60,000 to $74,999). Median household

U.S. Census Bureau, American Community Survey 5‐Year Estimates Cities: 2006‐2010 (S1901) Neighborhoods: 2007‐2011 (B19013)

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across the county. Identifying areas in the county with lower median incomes can help allocate resources for health promotion.

income was calculated using linear interpolation from the income range into which the household at the median fell. For cities, median household income was generated by the U.S. Census. For more information, see http://www.census.gov/hhes/www/p60_243sa.pdf

Families below 185% FPL The Federal Poverty Level (FPL) is a poverty threshold determined by the federal government, taking into account family size and income. Families with incomes below 185% FPL are eligible for some public assistance programs. Family poverty is associated with reduced access to goods and services, poorer physical and mental health, and higher mortality. 9 Furthermore, neighborhoods with higher concentrations of poverty may experience higher crime rates, community disinvestment, or other impacts, which may exacerbate the effects of individual and family poverty.10

Percentage of families below 185% of the Federal Poverty Level Sum of estimated number of families whose income ratio fell below 0.5, 0.5‐0.74, 0.75‐0.99, 1.00‐1.24, 1.25‐1.49, 1.50‐1.74, and 1.75‐1.84 of the Federal Poverty Level, divided by the number of families in a small area/neighborhood or city.

U.S. Census Bureau, American Community Survey 5‐Year Estimates Cities: 2006‐2010 (B17026) Neighborhoods: 2007‐2011 (B17026)

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Children (ages 0‐17) below 185% FPL

See above for a description of the Federal Poverty Level. Children from families who earn below 185% FPL are eligible for programs such as free or reduced price school lunch. Children who grow up in poverty may experience poor health and social and cognitive development, which can have profound effects on health later in life.11 12 Areas with higher concentrations of poverty in general may experience higher crime rates, community disinvestment, or other impacts, which may exacerbate the effects of individual child poverty.13

Percentage of population ages 0‐17 below 185% of the Federal Poverty Level Sum of estimated number of children living in families whose income ratio fell in the following categories: 0.5, 0.5‐0.74, 0.75‐0.99, 1.00‐1.24, 1.25‐1.49, 1.50‐1.74, and 1.75‐1.84, divided by the population ages 0‐17 in a small area/neighborhood or city.


Children (ages 3‐5) who are enrolled in preschool or nursery school

School preparedness is associated with school achievement in the later grades, a contributing factor to educational attainment.14 Identifying areas in the county with a lower proportion of children who are kindergarten ready can help allocate resources for supplemental education programs.

Percentage of children ages 3‐5 enrolled in preschool or nursery school


Educational attainment (ages >25 years)

Education is linked to health by providing higher employment and income levels as well as safer and healthier working

Percentage of population ages 25 and older with educational attainment in the following categories: less than 9th grade

U.S. Census Bureau, American Community Survey 5‐Year Estimates

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conditions. It also provides a foundation for improved health over the lifespan by building the knowledge and cognitive abilities that can help people make healthier behavioral choices, access social support, and assess health risks.151617 Communities with lower educational attainment among adults may benefit from interventions to assist with job training and economic development, as well as public health interventions to assist residents with making healthy choices.

or 9th to 12th grade no diploma, high school graduate (includes equivalency), some college or associate’s degree, and bachelor’s degree or graduate or professional degree

Cities: 2006‐2010 (DP02)

Neighborhoods: 2007‐2011 (B15002)

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HealthyandSafeEnvironmentIndicator Significance to public health How the measure was


Number of vehicle‐pedestrian injury collisions, 10 years

Pedestrian safety is an important factor in encouraging people to walk more. Pedestrian safety is especially important for promoting walking to school among children, as high numbers of collisions may discourage walking.18

Number of vehicle‐pedestrian injury collisions over a 10‐year period in a small area/neighborhood or city Number of collisions for Santa Clara County in the small area/neighborhood profiles is the average number of collisions by small area/neighborhood, adjusted for small area/neighborhood population size (weighted average). Number of collisions for Santa Clara County in the city profiles is the total number of collisions in the county over a 10‐year period.

Safe Transportation Research and Education Center (SafeTREC), Statewide Integrated Traffic Records System (SWITRS) Cities: 2006‐2010 Neighborhoods: 2002‐2011

Number of vehicle‐bicycle injury collisions, 10 years

Safer roads can encourage more people to ride bicycles for transportation and leisure. Higher rates of vehicle‐bicycle collisions may discourage biking among residents.19

Number of vehicle‐bicycle injury collisions over a 10‐year period in a small area/neighborhood or city

Number of collisions for Santa Clara County in the small area/neighborhood profiles is the average number of collisions by small area/neighborhood, adjusted for small area/neighborhood

Safe Transportation Research and Education Center (SafeTREC), Statewide Integrated Traffic Records System (SWITRS) Cities: 2006‐2010 Neighborhoods: 2002‐2011

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population size (weighted average). Number of collisions for Santa Clara County in the city profiles is the total number of collisions in the county over a 10‐year period.

Number of motor vehicle collisions, 1 year

Motor vehicle collisions are a leading cause of injury and mortality in the population.20 High rates of motor vehicle collisions in some areas may also deter area residents from walking and biking.

Number of motor vehicle collisions over a 1‐year period in a small area/neighborhood Number of collisions for Santa Clara County in the small area/neighborhood profiles is the average number of collisions by small area/neighborhood, adjusted for small area/neighborhood population size (weighted average). Number of collisions for Santa Clara County in the city profiles is the total number of collisions in the county over a 10‐year period.

Safe Transportation Research and Education Center (SafeTREC), Statewide Integrated Traffic Records System (SWITRS) Neighborhoods: 2011

Lives within ½ mile of a regional bus/rail/ferry and within ¼ mile of bus/light rail

Living near public transportation is associated with increased physical activity and reduced reliance on driving.21

Percentage of residents that live within ½ mile of a regional bus/rail/ferry and within ¼ mile of bus/light rail Half mile and ¼ mile buffers were created around transit stops, dependent on whether a stop was classified as local or

Metropolitan Transportation Commission 2010

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regional by the local transit agency. Census blocks with centroids inside ½ and ¼ mile buffers of the transit stops were identified and population counts were summed by census tract and then by small area/neighborhood. The percentage with access was calculated using small area/neighborhood population size. For more information, see http://www.cdph.ca.gov/programs/Documents/HCI_RailFerryBus_51_Narrative_and_examples_11‐26‐13SoCal_MTC_Sac.pdf

Residents who commute to work Commute modes, such as driving, biking, and using public transportation can affect the air quality in a community. Air quality is associated with adverse health effects such as increased mortality and morbidity from heart disease, respiratory illness, and some forms of cancer. 22 Using forms of active transportation to get to work is also associated with better health.23

Percentage of workers who commute to work by driving alone, carpooling, using public transit, or other means (walk to work, work from home, or commute to work by some other means)


Households receiving CalFresh benefits

CalFresh is a publicly‐funded program for supplemental food

Percentage of households with food stamp/SNAP benefits in

U.S. Census Bureau, American Community Survey 5‐Year

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assistance (also known as the Supplemental Nutrition Assistance Program, or SNAP). The proportion of residents receiving CalFresh can indicate individuals who may be at risk for experiencing food insecurity or a need for other nutritional services. Understanding the percentage of residents who receive CalFresh may help to target complementary nutritional programs.

the past 12 months Estimates Cities: 2006‐2010 (DP03) Neighborhoods: 2007‐2011 (S2201)

Average distance (miles) to nearest full‐service grocery store

Living near large grocery stores or supermarkets provides residents with greater access to a wide variety of healthy foods like fruits and vegetables.24

Average distance in miles to nearest full‐service grocery store Walking or driving distance in miles was calculated from each census block centroid to nearest full‐service grocery store. For cities and for Santa Clara County, the average distance was calculated based on block distance, adjusting for census block population size (weighted average). Full‐service grocery stores include supermarkets and large grocery stores. Supermarkets defined as food retailers with

InfoUSA 2012

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50 employees or more, large grocery stores as 10 to 49 employees.

Average distance (miles) to nearest farmers’ market

Farmers’ markets provide residents with additional access to locally‐produced healthy foods such as fresh fruits and vegetables.25

Average distance in miles to nearest farmers’ market Distance in miles from each census block centroid was calculated to nearest farmers’ market. For cities and for Santa Clara County, the average distance was calculated based on block distance (simple average).

Santa Clara County Division of Agriculture 2012

Number of fast food outlets per square mile

Communities with high numbers of fast food outlets may experience higher rates of overweight/obesity and chronic disease. Children are particularly vulnerable to the adverse health effects when attending schools near fast food restaurants.26

Number of fast food outlets divided by the number of square miles in a small area/neighborhood or city

Number of outlets per square mile for Santa Clara County in city and small area/neighborhood profiles calculated by summing the total number of outlets in cities and dividing by the total number of square miles in cities (excludes unincorporated areas).

InfoUSA 2012

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Households with gross rent 30% or more of household income

Households that face high housing costs may have reduced financial resources for other needed goods and services. High rent burden may mean that families have to move frequently or reside in communities with poorer quality housing and higher crime rates.27

Percentage of households with gross rent 30% or greater of household income


Overcrowded households Overcrowding in households is associated with adverse physical and mental health and can negatively affect children’s development.28 Identifying communities with a high percentage of overcrowded households may help target services and allocate resources around affordable housing.

Percentage of households with greater than one occupant per room


Lives in multi‐unit housing Multi‐unit housing residents may experience disproportionate exposure to secondhand smoke at home as a result of breathing in exhaled smoke and burning cigarettes from nearby smokers. People residing in multi‐unit housing may be exposed to smoke even if no one in their household smokes and may be at risk for developing heart disease, respiratory illness, some cancers, and other adverse

Percentage of households that reside in housing with two or more units in a structure


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health outcomes.29 Public health intervention efforts have focused on reducing exposure to secondhand smoke in multi‐unit housing.30

Average distance (miles) to nearest park or open space

Access to parks and open space are an important for encouraging exercise. Proximity to parks has been shown to increase levels of physical activity and improve overall health.31

Average distance in miles to nearest park or open space Distance in miles from each census block centroid was calculated to nearest boundary of a park or accessible open space, based on the straight‐line distance method (actual access points not available for analysis). For small areas/neighborhoods, census tract average distance was then calculated, adjusting for census block population size (weighted average) and then averaged by small area/neighborhood (simple average). For cities and for Santa Clara County, average distance for was calculated based on block distance, adjusting for census block population size (weighted average). Excludes parks with restricted

California Protected Areas Database 2011, Santa Clara County Parks Department 2012

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access, inaccessible parks, and special purpose open space areas such as golf courses and future unimproved park lands.

Number of tobacco retail outlets per square mile

The location of tobacco retail outlets in communities affects tobacco product availability, especially among adolescents who may be more likely to initiate tobacco use if residing in and/or attending school in areas with high densities of tobacco retailers.32

Number of tobacco retail outlets divided by number of square miles in small area/neighborhood or city Number of outlets per square mile for Santa Clara County in the city and small area/neighborhood profiles calculated by summing the total number of outlets in cities and dividing by the total number of square miles in cities (excludes unincorporated areas).

California Board of Equalization, November 2012

Average number of violent crimes within 1 mile

Violence is a cause of injury, disability, poor mental health, and premature death.33 Living in a community with a high number of violent crimes may also discourage residents from being physically active.34

Average number of violent crimes within 1 mile Number of violent crimes occurring within 1 mile of the each census block was calculated. For small areas/neighborhoods, average number for census tracts was then calculated, adjusting for census block population size (weighted

Public Engines, Inc., August 1, 2010‐July 31, 2011 (a standardized crime reporting system which reports crime for 15 crime types based on uniform crime reporting (UCR) definitions)

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average) and then averaged by small area/neighborhood (simple average). For cities and for Santa Clara County, the average number of violent crimes within 1 mile was calculated based on block counts, adjusting for census block population size (weighted average). Incidents coded as robbery, homicide, sexual assault and assault with a deadly weapon were defined as violent crimes, according to the definition provided by the FBI’s Uniform Crime Reporting (UCR) Program. Excludes incidents with reporting location in same block as a major hospital or police station, or which had a duplicate incident identifier.

Number of alcohol retail outlets per square mile

Communities with many liquor stores may have higher rates of alcohol‐related motor vehicle accidents and violent crime.35

Number of alcohol retail outlets divided by the number of square miles in a small area/neighborhood or city Number of outlets per square mile for Santa Clara County in the city and small area/neighborhood profiles

Department of Alcoholic Beverage Control (ABC), December 2012

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Healthstatus

was calculated by summing the total number of outlets in cities and dividing by the total number of square miles in cities (excludes unincorporated areas).

Indicator Significance to public health How this measure was calculated

Data source

Births per 1,000 people The birth rate is an important indicator of population growth. Information on areas with higher birth rates may assist agencies and organizations in deciding where to locate maternal and child health programs.

Number of births, divided by total population size, presented as a rate per 1,000 people

Santa Clara County Public Health Department, 2009‐2011 Birth Statistical Master File; U.S. Census Bureau, 2010 U.S. Census

Low birth weight infants Low birth weight is a risk factor for infant mortality. Low birth weight infants who survive their first year are at increased risk for physical and developmental complications.36 Communities with high rates of low birth weight may benefit from public health interventions, such as maternal/child health services.

Percentage of infants who weighed less than 2500 grams (5 pounds, 8 ounces) at birth

Santa Clara County Public Health Department, 2009‐2011 Birth Statistical Master File

Preterm births Prematurity is a risk factor for neurological problems, cardiovascular complications,

Percentage of infants born before 37 weeks of gestation

Santa Clara County Public Health Department, 2009‐2011 Birth Statistical Master File

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infections, and other health problems. Premature birth contributes to low birth weight and also increases the risk of infant mortality.37 Communities with high rates of preterm births may benefit from public health interventions, such as maternal/child health services.

Overweight or obese during first trimester of pregnancy

High pre‐pregnancy body mass index (BMI) measures the percentage of women who were overweight or obese before they became pregnant. A high BMI during pregnancy may increase the risks for developing gestational diabetes, preeclampsia, the risk of having a child with a high birth weight, and other adverse health outcomes.38 Communities with larger percentages of mothers with high maternal pre‐pregnancy BMI may benefit from behavioral and environmental interventions, such as physical activity and nutrition programs, as well as healthcare interventions regarding weight maintenance.

Percentage of women with live births who had a BMI of 25.0 or higher (overweight or obese) during the first trimester

California Department of Public Health, 2009‐2011 Birth Statistical Master File

Mothers who received early and adequate prenatal care

Prenatal care is important for determining potential pregnancy complications early

Percentage of women with live births who received early and adequate prenatal care

California Department of Public Health, 2009‐2011 Birth Statistical Master File

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on and is associated with reductions in maternal and infant deaths, miscarriages, birth defects, low birth weight, and other preventable problems. 39 Communities with lower percentages of early and adequate care may benefit from improved access to healthcare for woman of childbearing age.

Early and adequate prenatal care, also known as the Kotelchuck Index is defined as care initiated by the fourth month and receiving at least 80% of recommended prenatal visits.40

Teen live births per 1,000 females ages 15‐19

Teenage births are associated with lower income and higher school dropout rates for mothers, as well as lower earning potential for fathers.41 Infants born to teenage mothers are at increased risk of low birth weight, poorer nutrition, and lower cognitive and social stimulation, which can lead to lower academic achievement later in life.42 Communities with higher teen birth rates may benefit from public health interventions concerning sex and sexuality and improved access to healthcare for teen females.

Number of live births among female adolescents ages 15‐19, divided by the total number of female adolescents ages 15‐19, and presented as a rate per 1,000 females ages 15‐19.

California Department of Public Health, 2009‐2011 Birth Statistical Master File; U.S. Census Bureau, 2010 U.S. Census

Life expectancy Life expectancy is an important indicator of the overall health status of a population.43 Life expectancy is defined as the average number of years a

Life expectancy was calculated based on Santa Clara County mortality data over a 5‐year period. For more information on how to calculate life

Santa Clara County Public Health Department, 2008‐2012 Death Statistical Master File; U.S. Census Bureau, 2010 U.S. Census

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population of a certain age would be expected to live, given a set of age‐specific death rates in a given year. Life expectancy may vary by where people live. Areas with lower life expectancy may experience higher levels of poverty, lower levels of educational attainment, and other factors associated with premature mortality.44

expectancy, see: http://www.cdc.gov/nchs/data/nvsr/nvsr61/nvsr61_03.pdf.

Cancer deaths per 100,000 people Cancer is one of the leading causes of death in Santa Clara County. Communities with higher cancer mortality may benefit from behavioral or environmental interventions, such as smoking cessation, improved cancer screening, and healthcare access.

Number of people who died from cancer, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.

Santa Clara County Public Health Department, 2008‐2012 Death Statistical Master File ; U.S. Census Bureau, 2010 U.S. Census

Heart disease deaths per 100,000 people

Heart disease is a cause of premature death and is one of the leading causes of death in Santa Clara County. Several factors may increase the risk of heart disease, namely being overweight or obese, poor nutrition, limited physical activity, smoking, and alcohol use. Hypertension (high blood

Number of people who died from heart disease (includes heart attacks and other diseases of the heart excluding stroke), age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see


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pressure) and high cholesterol also increase the risk of heart disease. Communities with higher rates of heart disease may benefit from behavioral or environmental interventions, such as physical activity or nutrition programs.

http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.

Alzheimer’s disease deaths per 100,000 people

Alzheimer’s disease is one of the leading causes of death in Santa Clara County. Communities with higher rates of Alzheimer’s disease may have a greater need for elder care services and centers.

Number of people who died from Alzheimer’s disease, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.


Stroke deaths per 100,000 people Stroke is one of the leading causes of death in Santa Clara County. Health behaviors such as poor nutrition, limited physical activity, smoking, and alcohol use may increase the risk of having a stroke. Communities with higher rates of mortality from strokes may benefit from behavioral or environmental interventions, such as smoking cessation.

Number of people who died from stroke, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.


Chronic lower respiratory disease Chronic lower respiratory Number of people who died Santa Clara County Public Health

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deaths per 100,000 people disease, which includes asthma, chronic obstructive pulmonary disease (COPD), emphysema, and bronchitis, is one of the leading causes of death in Santa Clara County. Smoking is a risk factor for COPD. Asthma symptoms may be exacerbated by exposure to air pollution and poor air quality. Communities with higher rates of mortality from COPD may benefit from behavioral or environmental interventions, such as smoking cessation, mold reduction, and reduction in vehicle emissions near residential areas.

from chronic lower respiratory disease, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.

Department, 2008‐2012 Death Statistical Master File ; U.S. Census Bureau, 2010 U.S. Census

Unintentional injury deaths per 100,000 people

Unintentional injury, a cause of premature death, include motor vehicle crashes, falls, poisonings, suffocations, and drowning, Unintentional injury is one of the leading causes of death in Santa Clara County. Unintentional injury may result from residing in an unsafe environment or not taking appropriate safety precautions, such as not wearing seatbelt when driving.

Number of people who died from unintentional injury, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.


Diabetes deaths per 100,000 people

Diabetes is a leading cause of death in Santa Clara County.

Number of people who died from diabetes, age‐adjusted

Santa Clara County Public Health Department, 2008‐2012 Death

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People are at higher risk for developing diabetes if they have poor nutrition, limited physical activity, or are obese. Diabetes is a risk factor for heart disease, blindness, and kidney failure. Communities with higher rates of mortality from diabetes may benefit from behavioral or environmental interventions, such as smoking cessation or physical activity and nutrition programs.

using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.

Statistical Master File ; U.S. Census Bureau, 2010 U.S. Census

Influenza and pneumonia deaths per 100,000 people

Influenza and pneumonia are one of the leading causes of death in Santa Clara County. Communities with higher rates of mortality from influenza and pneumonia may benefit from public health interventions, such as vaccination programs, and from improved access to healthcare.

Number of people who died from influenza and/or pneumonia, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.


Hypertension deaths per 100,000 people

Hypertension, also known as high blood pressure, is a risk factor for heart disease and stroke. Communities with higher rates of mortality from hypertension may benefit from behavioral interventions, such as smoking cessation, as well as

Number of people who died from hypertension, age‐adjusted using the direct method and the 2000 projected U.S. population. Presented as a rate per 100,000 people. For more on age adjustment, see


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improved access to healthcare. http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Rates are not reported for indicators with fewer than 20 deaths.

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Limitations and additional technical notes

Data from the American Community Survey were pooled for contiguous census tracts to derive demographic, economic, educational, and health and safety indicators. For categorical indicators, the estimated number of residents with a particular characteristic, e.g., the number in a particular age range, in contiguous census tracts in a given small area/neighborhood were summed. This sum was then divided by the sum of the estimated number of residents in contiguous census tracks in a given small area/neighborhood and multiplied by 100 to produce a percentage (see individual indicators for more information on calculations for continuous data). Because ACS estimates are based on a sample of each census tract, and not on a full enumeration as with the U.S. Census, sampling error should be accounted for when making inferences. Data are for descriptive purposes only. Inferences and comparisons should be avoided because sampling errors are not included on this profile.

All information on health and social indicators on all surveys utilized in the profiles was self‐reported and so is subject to reporting bias. Public health surveillance data (births, deaths, and infectious disease) utilized in the profiles were subject to both misclassification and reporting bias; however, this bias is expected to be minimal. 1 Murray CJL, Kulkarni SC, Michaud C, Tomijima N, Bulzacchelli MT, et al. (2006) Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race‐Counties in the United States. PLoS Med 3(9): e260. doi:10.1371/journal.pmed.0030260 2 Public Policy Institute of California (2008). Just the Facts: Immigrants and Health. <http://www.ppic.org/content/pubs/jtf/JTF_ImmigrantsHealthJTF.pdf> 3 Bramlett, M.D. and S.J. Blumberg (2007). Family Structure and Children’s Physical and Mental Health. Health Affairs, 26 (2). 4 Krieger, J., & D.L. Higgins (2002). Housing and Health: Time Again for Public Health Action. American Journal of Public Health, 92(5). 5 Strully KW (2009). Job loss and Health in the U.S. Labor Market. Demography, 46(2). 221‐246. 6 Lin, R.L., Shah, C.P. and T.J. Svoboda (1995). Canadian Medical Association, 529‐666. 7 Strully KW (2009). Job loss and Health in the U.S. Labor Market. Demography, 46(2). 221‐246. 8 Marmot, M. (2002). The influence of income on health: Views of an Epidemiologist. Health Affairs, 31‐46. 9 Ratcliffe, C and SM McKernan (2010). Childhood Poverty Persistence: Facts and Consequences. The Urban Institute. Brief 14. 10 Krieger, J., & D.L. Higgins (2002). Housing and Health: Time Again for Public Health Action. American Journal of Public Health, 92(5). 11 Shonkoff, J.P., Garner A.S., et al (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), 232‐246. 12 Ratcliffe, C and SM McKernan (2010). Childhood Poverty Persistence: Facts and Consequences. The Urban Institute. Brief 14. 13 Krieger, J., & D.L. Higgins (2002). Housing and Health: Time Again for Public Health Action. American Journal of Public Health, 92(5). 14 Duncan, G.J., et al (2007). School readiness and later achievement. Developmental Psychology, 1428‐1446. 15 Catherine E. Ross and Chia‐Ling Wu, “The Links Between Education and Health,”, American Sociological Review 60, no. 5 (1995): 719. 16 Catherine E. Ross and Chia‐Ling Wu, “Education, Age and the Cumulative Advantage in Health”, Journal of Health and Social Behavior 37, no. 1 (1996): 104‐120. 17 Robert Wood Johnson Foundation. Education and Health (2011). Exploring the Social Determinants of Health Issue #6. 18 Jacobsen, P. R. (2009). Who owns the roads? How motorized traffic discourages walking and bicycling. Injury Prevention, 369‐373. 19 Marshall, W. G. (2011). Evidence on why bike‐friendly cities are safer for all road users. Environmental Practice, 16‐27.

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