Descriptive Title: Proportion of households likely to move away from San Francisco in the next three years

Geographic Unit of Analysis: Zip code

Proportion of Households Likely to Move Away in the Next Three Years (2011)
Zip Code Neighborhoods Very Likely Somewhat Likely Not Too Likely Not Likely At All
All San Francisco 8% 17% 27% 46%
94102 Downtown Civic Center  13% 14% 29% 41%
94103 SOMA 11% 20% 30% 36%
94104 Financial District na na na na
94105 Financial District na na na na
94107 Potrero Hill, SOMA 11% 30% 26% 32%
94108 Nobb Hill, Financial District 5% 12% 27% 55%
94109 Downtown Civic Center, Nob Hill, Russian Hill 11% 17% 30% 38%
94110 Mission, Bernal Heights 8% 15% 26% 49%
94111 Financial District, North Beach na na na na
94112 Outer Mission, Ocean View, Crocker Amazon 4% 15% 22% 55%
94114 Castro, Noe Valley 4% 16% 31% 49%
94115 Western Addition, Pacific Heights 8% 20% 27% 40%
94116 Parkside, Outer Sunset 4% 14% 26% 52%
94117 Haight Ashbury 8% 17% 31% 41%
94118 Inner Richmond, Presidio Heights 9% 19% 30% 38%
94121 Outer Richmond, Seacliff 9% 11% 28% 49%
94122 Outer / Inner Sunset, Golden Gate Park 6% 19% 26% 44%
94123 Marina, Russian Hill 11% 21% 32% 34%
94124 Bayview 8% 11% 24% 52%
94127 West of Twin Peaks, Ocean View 4% 10% 19% 66%
94129 The Presidio na na na na
94130 Treasure Island na na na na
94131 Diamond Heights / Glen Park, Twin Peaks, Inner Sunset 6% 15% 23% 52%
94132 Lakeshore, Ocean View 5% 17% 26% 46%
94133 Russian Hill, North Beach 4% 20% 27% 46%
94134 Visitacion Valley, Excelsior 4% 17% 19% 56%
94158 Mission Bay na na na na

Why Is This An Indicator Of Health and Sustainability?

Residents' plans to stay in their communities may reflect social networks and feelings of belonging among community members. Neighborhoods that experience less residential mobility are more likely to develop lasting, supportive social networks among residents than neighborhoods with high residential mobility.

Social networks and social integration are beneficial to health: Healthy People 2010 asserts that the social environment—including interactions with family, friends, coworkers, and others in the community—has a "profound effect on individual health."a For example, social support can buffer people from the negative psychological effects of life stress.b One review of over 100 studies concluded that social support for pregnant women improves fetal growth.c Other studies have found that women who receive social support have healthier babies, fewer complications in pregnancy and birth, and less postpartum depression.d

Emile Durkheim's work on suicide showed that the lowest rates of suicide occurred in societies with the highest degrees of social integration.e In Alameda County in 1979, researchers found that men and women who lacked ties to others were 1.9 to 3.1 times more likely to die during the follow-up period than those who had many contacts.f Other studies have linked specific health conditions—such as strokes, death from cardiovascular disease, and the common cold—to having fewer social ties.c,g

Interpretation and Geographic Equity Analysis

This indicator illustrates the responses from San Francisco residents who participated in the 2011 City Survey about how likely they are to move away from San Francisco in the next three years.  The map and table present answers by zipcode. 

In the following zipcode neighborhoods, more than 10% of respondents surveyed stated that they are very likely going to move away in the next three years: Downtown/Civic Center (94102/94109), South of Market (94103/94107), Potrero Hill (94107), Russian Hill/the Marina (94123) and Nob Hill (94109).   In the following zipcode neighborhoods, 55% or more of respondents surveyed stated that they are not likely going to move away in the next three years: West of Twin Peaks (94127), Ocean View (94127/94112), Visitacion Valley/Excelsior (94134), Outer Mission/Crocker Amazon (94112), and the Financial District/Nob Hill (94108). 

As illustrated on the map for Indicator H.1.d Home Ownership, the likelihood of moving away correlates closely with proportion of owner-occupied households. Recent events such as the dot-com boom in the late 1990s, the recent mortgage foreclosure crisis and rise in unemployment rates have significantly impacted residential demographics and mobility in the Bay Area.  Certain communities, particularly low-income communities of color, have been disproportionately affected by the changes and resulting demographic shifts. 

Over the past forty years, the African American community in particular has experienced significant residential mobility.  According to a 2009 report by the Mayor’s Task Force on African-American Out-Migration, the number of African Americans residing in San Francisco in 1970 was about 88,000. By 2005, the number had dropped to 46,779.  Between 1990 and 2000, the number of African American households decreased by 20.3%, while the number of non-African American households increased by 11%.h

Although the data is not presented above, the City Survey also provides resident responses to the question by respondent’s race/ethnicity.  According to the 2011 City Survey, a higher percentage of respondents of Mixed Ethnicity/Other (10.4%), Black/African Americans (9.4%) and Native American Indians (9.1%) were “very likely” to move away from San Francisco than Asian/Pacific Islanders (7.3%), Latinos/Hispanics (7.3%), or Whites/Caucasians (7.9%).  

Methods

The City Survey is conducted annually by the San Francisco Controller's Office in order to measure residents' opinions about the quality and level of City services.   1000 residents were randomly selected from each supervisorial district and 3,979 mail, phone, and web surveys were completed for a response rate of 37% when accounting for undeliverable surveys.  The survey was available in English, Spanish, and Chinese.  The overall distribution of survey respondents’ demographics was determined to be similar to the most recent census estimates and so no additional sampling was conducted.

The question used to construct this map and table was, "In the next three years, how likely are you to move out of San Francisco?" The possible answers were "very likely," "somewhat likely," "not too likely," or "not at all likely." A total of 3979 respondents answered this question. The table shows the percent of respondents in each zipcode who gave each answer. The map shows the percent of respondents in each zipcode who answered that they were either "very likely" or "somewhat likely" to move out of San Francisco in the next three years.

For more information, the City Survey Report 2011—including information about the survey responses and methodology and a sample survey questionnaire—is available at: http://co.sfgov.org/webreports/details.aspx?id=1343.

Limitations

Since each zip code may contain one or more neighborhoods, it is not possible compare the answers given by people living in different neighborhoods within the zip code. It is also important to remember that different respondents may have given the same answers, but for different reasons: for example, some residents may plan to stay in the same community because they are happy there, while others may feel they lack the resources to move. This indicator does not give any information about residents' plans to move within the city of San Francisco.

Neighborhood social cohesion is not a time-static concept; movement of residents, organizations, and businesses into and out of a neighborhood can impact the social dynamics among neighbors and other components of social cohesion. While this indicator provides a snapshot of one aspect of social cohesion, it does not provide any information about long-term trends. Residents' plans to stay in their communities represent one among many possible indicators of social cohesion within a neighborhood.

Taken alone, the fact that residents do not think they are likely to leave San Francisco does not necessarily mean that a neighborhood is socially cohesive. Similarly, it is possible for a neighborhood to be socially cohesive even if residents do not plan to stay in San Francisco. In general, neighborhood-level indicators may obscure ethnic, class, or other differences among the neighborhood population. For example, residents' plans to stay in San Francisco may indicate good social cohesion among some groups, but others may not feel integrated into the social fabric for a variety of reasons, such as the language(s) spoken, cultural or religious preferences, or physical accessibility. Thus social cohesion may be advanced for some groups while others may feel excluded.

Data Source

Data from the San Francisco City Survey Report 2011 by the City and County of San Francisco, Office of the Controller. Available at: http://co.sfgov.org/webreports/details.aspx?id=1343

Map and table created by San Francisco Department of Public Health, Environmental Health Section using ArcGIS software.

Table data is presented by supervisoral district.

Detailed information regarding census data, geographic units of analysis, their definitions, and their boundaries can be found at the following links:

Interactive boundaries map

http://sfindicatorproject.org/resources/data_map_methods

  1. Healthy People 2010, Office of Disease Prevention and Health Promotion, U.S. Department of Health and Human Services. Available at: http://www.healthypeople.gov/
  2. Cohen S, Underwood LG, Gottlieb BH, eds. 2000. Social Support Measurement and Intervention: A Guide for Health and Social Scientists. New York: Oxford University Press.
  3. Kawachi I, Colditz GA, Ascherio A, Rimm EB, Giovannucci E, Stampfer MJ, Willett WC. 1999. A Prospective study of social networks in relation to total mortality and cardiovascular disease incidence in men in the United States. Pp. 184-194 in The Society and Population Health Reader. Volume I: Income Inequality and Health, eds. I. Kawachi, BP Kennedy, RG Wilkinson. New York: The New Press.
  4. Berkman LF. 1999. The Role of social relations in health promotion. Pp. 172-183 in The Society and Population Health Reader. Volume I: Income Inequality and Health, eds. I. Kawachi, BP Kennedy, RG Wilkinson. New York: The New Press.
  5. Berkman LF, Kawachi I. 2000. A Historical Framework for Social Epidemiology. Chapter 1 in Social Epidemiology. New York: Oxford University Press.
  6. Berkman LF, Syme SL. 1979. Social networks, host resistance and mortality: a nine-year follow up study of Alameda County residents. American Journal of Epidemiology 109:186-204.
  7. Cohen C, Doyle WJ, Skoner DP, Rabin BS, Gwaltney JM. 1997. Social ties and susceptibility to the common cold. JAMA 277(24):1940-1944.
  8. Report of the San Francisco Mayor’s Task Force on African-American Out-Migration.  2009.  http://www.sfredevelopment.org/Modules/ShowDocument.aspx?documentid=292