- SELF-SUFFICIENCY INCOME
- EDUCATIONAL ATTAINMENT
- LABOR FORCE PARTICIPATION
- EMPLOYMENT RATE
- MEDIAN HOUSEHOLD INCOME
- INCOME INEQUALITY
In this assessment, economic environment refers to measures that illustrate the educational, employment, earning, and self-sufficiency status of the adult population.
Researchers have consistently found that a person’s social class is the most important predictor of health . Education, occupation, income, and wealth are all elements of social class that impact health, because in the United States they generally determine the extent to which individuals and communities can access and consume resources that build health, such as things like health care, healthy food, and the ability to live in a safe and clean neighborhood [2-4]. Additionally, and perhaps even more importantly, higher social class often confers individuals with a greater sense of control over their lives, which reduces the overall burden of stress on their bodies [3, 5].
Education is foundational for developing the knowledge and skills that are needed for gainful employment. In the adult working-age population, education is typically measured as “educational attainment,” or the years or level of overall schooling a person has achieved. In general, college graduates can expect to live five years longer than individuals who have not finished high school . Educational attainment impacts health in many ways, including by influencing a person’s employment and income. Americans with lower educational attainment are more likely to be affected by fluctuations in the economy and to experience unemployment. In 2009, unemployment rates were 15.5% for adults without a high school diploma, but 4.7% for college graduates . When employed, workers with less formal education are more likely to be employed in hazardous jobs, receive less health-related benefits and earn lower incomes . Additionally, less-educated, low-paid workers are less likely to have control over many aspects of their working conditions, including hours and schedules, the balance between effort and rewards, decision latitude, organizational justice, and social support at work . These factors can all contribute to physical and psychological stress that impedes health.
The influence of income on health begins early in life. Income has been linked to rates of low birth weight, which has been linked to child development and chronic disease later in life . Children in lower-income families are also more likely to experience asthma, heart conditions, digestive disorders, and have elevated blood lead levels . Poor adults are nearly five times as likely to report being in poor or fair health as adults with incomes over 400% of the Federal Poverty Level [4.] Wealth is the amount of financial assets that an individual has to draw upon minus debts owed. While less studied in relation to health than income, wealth is an important aspect of economic well-being because it allows individuals and families to weather storms like unemployment, medical issues, or other catastrophes. In addition, wealth (most often in the form of home ownership) tends to be passed down from generation to generation. Institutionalized racism, such as discriminatory housing policies and predatory lending practices, have had generational impacts by preventing the accumulation of wealth in many communities of color . Income and wealth influence health through multiple pathways, including access to health promoting goods and services, such as health food, safe housing and timely medical care; the psychosocial effects linked with economic resources, including less control over working conditions and the ability to pay for basic needs; and the cumulative impact of economic deprivation during critical periods, like pregnancy and childhood .
In addition to individual and family level impacts, numerous studies have shown that income inequality, the extent to which income is distributed in an uneven manner among a population, is strongly and independently associated with decreased life expectancy and higher mortality, as well as reduced self-rated health status.  The effects of income inequality are likely mediated financially by means of public investments in shared goods and services, and socially by means of social cohesion, intrapersonal trust, and reciprocity. Accordingly, places with relatively more egalitarian distributions of income would have a higher average life expectancy irrespective of the average level of income. 
For more information on the impacts of food security and housing affordability, please see the Nutrition and Housing sections of this assessment.
Based on per capita income, gross domestic product, median household income, and other indicators, the San Francisco Bay Area is one of the most prosperous in the nation . In 2016, the median household income in San Francisco was $103,801, ranking 14th among all US counties with a population of 65,000 or more . However, the increasing cost of living along with inequitable economic opportunity means that many in San Francisco are struggling to meet their basic needs.
Cost of Living: Because many social services are available only to those earning less than 180 – 200 percent of FPL, the high cost of living in San Francisco means that a significant number of those who don’t qualify for social services are in need. The Family Economic Self-Sufficiency Standard measures how much income is needed for a family, precisely defined and located in a particular county, to adequately meet its minimal basic needs. It is based on the costs families face on a daily basis — housing, food, childcare, out-of-pocket medical expenses, transportation, and other necessary spending — and provides a complete picture of what it takes for families to make ends meet. The average 2014 California self-sufficient standard for two adults and two children (one preschooler, one school-aged child) was $63,979, above the federal poverty guideline of $23,850 . In San Francisco, the self-sufficient standard for 2 adults, 1 infant, and 1 school aged child was $83,522 (Figure 1). On May 1, 2015, hourly minimum wage in San Francisco was increased to $12.25 and on November 4, 2014, San Francisco voters passed Proposition J, raising the minimum wage to $15.00 by 2018. Even with the increases, those earning minimum wage in 2018 will earn significantly less than is needed to live in San Francisco.
Housing and childcare represent the most significant living costs many for San Franciscans. Please see the housing and childcare and education data pages for more information about the economic burdens of these expenses for San Francisco families.
Educational attainment: On average, children from less economically privileged households have lower levels of educational attainment than their higher-income peers, and this association has important implications for equality of opportunity . Educational attainment is related to both income level and employment rate; those with higher educational attainment earn more and are less likely to be unemployed . Overall, San Franciscans have high educational attainment; a greater percentage of adults 25 and over (57%) have a bachelor’s degree or higher than in California (33%) (Figure 2). Overall, males and females have similar educational attainment in San Francisco (Figure 6). However, educational attainment varies, by ethnicity, age, and poverty level. A lower percentage of Asian, Black/African American, and Latino/a adults have at least a bachelor’s degree compared to whites (Figure 7). Younger generations are more likely to have bachelors degree or more – 72% of 25-35 year olds have a bachelor’s or more, compared to 29% of 55-64 year olds (Figure 8). About 26% of individuals living below 200% of the federal poverty level have a bachelor’s degree or higher, whereas 62% of persons living at or above 200% of the poverty level have a bachelors or higher (Figure 9). The neighborhoods with the lowest percent of residents with a bachelor’s or more are Chinatown, Visitacion Valley, Bayview, Excelsior, Portola, and OMI, which all have under 30% (Figure 3). Areas that are not designated as an Area of Vulnerability (AOV) have 65% of residents with a bachelors or more while 36% of residents that are in an AOV have advanced education (Figure 4).
Employment: A steady job in safe working conditions means more than simply a paycheck. Employment can also bring the income, benefits, and stability necessary for good health. Conversely, job loss and unemployment is associated with a variety of negative health effects. In terms of measuring participation in the workforce, there are two measures to track, labor force participation, or the percentage of the population 16 years and older that is either working or looking for work, and employment/unemployment rates. The employment rate is calculated by dividing the number of people that are working by the population that is in the labor force (e.g. retired persons and persons that do not want to work are left out). The years 2006, 2011, and 2012 represent low points for labor force participation in San Francisco; however, since 2013 labor force participation has been above 70% (Figure 2). In 2016, the unemployment rate in San Francisco was 4.5% – the lowest it has been in the past 10 years (Figure 2). When examined by gender, a lower percentage of females are in the labor force than males, but equal percentages of men and women are employed (Figure 6). Black/African American and Asian residents have the lowest labor force participation – 55% of BAA residents are in the labor force and 64% of Asian residents are, compared to 76% of White residents and 72% of Latino residents (Figure 7). Similarly, Black/African American and Pacific Islander residents have the lowest employment rates (83% and 84% respectively), while all other ethnic groups have employment rates over 90% (Figure 7). When examined by age group, the trends are what would be expected – higher percentages of people between the ages of 25-54 are in the labor force, after which labor force participation drops off (Figure 8). However, across ages the employment rate is similar (Figure 8). Only about 47% of persons living under 200% of the FPL are in the labor market, compared to 79% of the population living at 200% FPL or higher (Figure 9). The neighborhoods with the lowest labor force participation are Chinatown, Seacliff, Tenderloin, Lakeshore, and South of Market, which all have less than 60% participation (Figure 3). However, the neighborhoods with the lowest employment rates are Bayview, Lakeshore, OMI, and Visitacion Valley, which all have employment rates of less than 90% (Figure 3). Areas designated as an Area of Vulnerability have both lower labor force participation and employment rates (Figure 4).
Poverty: Federal poverty level (FPL) is a widely used indicator of poverty and is often used to determine eligibility for public services. In 2016 the FPL is $27,950 for a family of four. In San Francisco in 2016, 10 percent of residents lived below 100 percent of the federal poverty level and more than one in five residents lived below 200 percent FPL (Figure 2). In recent years the percent of the population living below 200% of the poverty level has significantly declined, from a high of 30% in 2011 to 22% in 2016. When examined by gender there is not a significant difference (Figure 6). Black/African American and Latino/a residents have the highest proportion of residents living below 200% FPL – 54% of BAA residents and 36% of Asian residents are, compared to 16% of White residents (Figure 7).When examined by age group, persons 75 years and older have the highest percent of persons living below 200% FPL (46%) (Figure 8). The neighborhoods with the highest proportion of residents living below 200% FPL are Chinatown, Tenderloin, Lakeshore, McLaren Park, and Treasure Island, which all have more than 50% very low-income residents (Figure 3). High proportions of low income residents in Lakeshore are likely related to a high density of SF State Students living there, and many of the residents in the McLaren Park analysis neighborhood living in the Sunnydale public housing development. The percent of residents living below 200% FPL is over twice as high in Areas of Vulnerability (41%) than elsewhere (17%) (Figure 4).
Median Income: In recent years, there has been a rapid increase in the median household income in San Francisco – from $69,894 in 2011 to $103,891 in 2016 (Figure 2). This makes San Francisco one of the most affluent counties in the country. The neighborhoods with the lowest median household income are Chinatown, Tenderloin, South of Market, Lakeshore, and Treasure Island, which all have median household incomes of under $50,000 (Figure 3). The neighborhoods with the highest household incomes are Seacliff, Presidio, and Potrero Hill, which all have median household incomes over $150,000 (Figure 3). Areas that are not designated as an Area of Vulnerability (AOV) have a median household income twice as high as areas that are designated as AOVs (Figure 4).
Income inequality: Income inequality metrics aim to describe inequalities in the distribution of income in a specific population. Some measures like the Gini coefficient are based on the entire distribution of income; others capture relative differences in incomes at specific points in the distribution or between different populations. There is significant income inequality in San Francisco. The Bay Area, and San Francisco in particular, have some of the highest income disparities in the United States.  In 2016 San Francisco had the second highest Gini coefficient (50) among the nine Bay Area counties, after Marin County (52) (Figure 5).
ACS American Community Survey. https://factfinder.census.gov/
ICCD Insight Center for Community Development, Self-Sufficiency Standard Tool for California. https://insightcced.org/tools-metrics/self-sufficiency-standard-tool-for-california/
Statistical instability: Statistically unstable estimates are not shown in this document. Statistical instability may arise from:
…few respondents to a survey,
…small population sizes, or
…small numbers of affected individuals.
Statistical instability indicates a lack of confidence in an estimates ability to accurately and reliably represent the population. Due to statistical instability, estimates are not available for all age, gender, ethnicity, or other groups.
Areas of Vulnerability: Areas of Vulnerability (AOV) were created as a way to examine geographic data in relation to populations of concentrated socioeconomic disadvantage. The criteria to be designated as an AOV were:
1) Top 1/3rd of tracts for < 200% poverty or < 400% poverty & top 1/3rd for persons of color OR
2) Top 1/3rd of tracts for < 200% poverty or < 400% poverty & top 1/3rd for youth or seniors (65+) OR
3) Top 1/3rd of tracts for < 200% poverty or < 400% poverty & top 1/3rd for 2 other categories (unemployment, completing high school or less, limited English proficiency persons, linguistically isolated households, or disability)
Tracts that had unstable data for an indicator were automatically given zero credit for that indicator.
 M. Walsh. Introduction to Sociology for Health Carers, chapter Social Class and health Experience, pages 49–63. Cheltenham UK: Nelson Thornes Ltd, 2004.
 Susan Egerter, Paula Braveman, Tabashir Sadegh-Nobari, Rebecca Grossman-Kahn, and Mercedes Dekker. Exploring the social determinants of health: Education and health: Education and health. Technical report, Robert Wood Johnson Foundation, 2011.
 Jane An, Paula Braveman, Susan Egerter, Mercedes Dekker, and Rebecca Grossman-Kahn. Exploring the social determinants of health: Workplaces and health. Technical report, Robert Wood Johnson Foundation, 2011.
 Paula Braveman, Susan Egerter, and Colleen Barclay. Exploring the social determinants of health: Income, wealth and health. Technical report, Robert Wood Johnson Foundation, 2011.
 Susan Egerter, Paula Braveman, and Colleen Barclay. Exploring the social determinants of health: Stress and health. Technical report, Robert Wood Johnson Foundation, 2011.
 Thomas Shapiro, Tatjana Meshede, and Sam Osoro. The roots of the widening racial wealth gap: Explaining the black-white economic divide. Technical report, Institute on Assets and Social Policy, 2013.
 John Lynch, George Davey Smith, Sam Harper, Marianne Hillemeier, Nancy Ross, George A Kaplan, and Michael Wolfson. Is income inequality a determinant of population health? part 1. a systematic review. The Milbank quarterly, 82:5–99, 2004.
 I. Kawachi. Social epidemiology, chapter Income Inequality and Health, pages 76–94. New York: Oxford University Press, 2000.
 Silicon Valley Institute for Regional Studies, June 2015, “Income Inequality in the San Francisco Bay Area.” http://siliconvalleyindicators.org/pdf/income-inequality-2015-06.pdf
 Wikipedia contributors. (2018, August 2). List of highest-income counties in the United States. In Wikipedia, The Free Encyclopedia. Retrieved 16:50, August 10, 2018, from https://en.wikipedia.org/w/index.php?title=List_of_highest-income_counties_in_the_United_States&oldid=853055531
 Insight Center for Economic Development, “Self Sufficiency Standard Tool for California.”
California Family Needs Calculator (formerly the Self-Sufficiency Standard Tool 2014)
 Owen Thompson, “Economic Background and Educational Attainment–The Role of Gene-Environment Interactions.” https://pantherfile.uwm.edu/thompsoo/www/JHR.pdf
 Bloomberg 2014, “Most Income Inequality: US Cities.”
Copyright sfhip 2022