Racial diversity is measured by a diversity index that is calculated using United States Census racial and ethnic population characteristics from the PL-94 data file. The diversity index is a quantitative measure of the distribution of the proportion of five major ethnic populations (non-Hispanic White, non-Hispanic Black, Asian and Pacific Islander, Hispanic, and Two or more races). The index ranges from 0 (low diversity meaning only one group is present) to 1 (meaning an equal proportion of all five groups is present). The diversity score for the United States in 2010 is 0.60. The diversity score for the San Francisco Bay Region is 0.84. Within the region, Solano (0.89) and Alameda (0.90) Counties are the most diverse and the remaining North Bay (0.55 - 0.64) Counties are the least diverse.

About this dataset

Context

The dataset presents the median household income across different racial categories in San Francisco township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of San Francisco township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 95.31% of the total residents in San Francisco township. Notably, the median household income for White households is $133,763. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $133,763.

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Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in San Francisco township.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for San Francisco township median household income by race. You can refer the same here

Population-adjusted prevalence of antibodies from COVID-19 vaccination in Round 3 within race/ethnicity and age groups and prevalence differences between non-White and White individuals.

This archive contains the ESRC funded data collection (UK data) only. The data collection contains a state file consisting of 902 variables, 677 observations. The codebook available in the data collection provides detailed descriptions of variables and data codes (missing etc). For more information please contact stephani.hatch@kcl.ac.uk Research from the United Kingdom and the United States shows wide health inequalities by race/ethnicity and socio-economic status. So far we do not clearly understand the roles that discrimination and social context play in creating these inequalities. Research teams at King's College London (UK) and Columbia University (USA) will carry out studies to investigate: the roles that the historical social context and policy play in shaping observed patterns of health inequalities; differences in anticipated and perceived experiences of discrimination; how discrimination contributes to inequalities in everyday social functioning, mental health, physical health, and use of health services. Comparisons will be made with 1600 adults from two larger studies, (i) the UK National Institute for Health Research-funded South East London Community Health study at the Biomedical Research Centre for Mental Health, and (ii) the US National Institute of Health-funded Child Health and Development Disparities Study in the East Bay Area of California. UK and US researchers, health practitioners, and community members will be invited to participate in developing the social and historical contextual narratives and in planning the dissemination of our research findings. South East London Community Health (SELCoH) study is a follow up study of the community psychiatric and physical morbidity of adults, age 16 years and over from randomly selected households in the south London boroughs of Southwark and Lambeth. Participants were identified through use of the random household sampling as described and used for the Household Survey of the National Survey of Psychiatric morbidity (1). The sample is stratified across the two boroughs to ensure a similar sample size for each area. Individuals were eligible for participation providing they lived in a household in the catchment area. No further exclusion criteria applied. Recruitment for phase 1 (hereafter SELCoH-I), was done between 2008 and 2010, with the final data-set containing information on 1698 adults, aged between 16 and 90 years, from 1075 randomly selected households across two London boroughs. Further details on SELCoH’s organisation, sample and procedures may be found elsewhere (2). Most (94%) of the SELCoHI study participants agreed to be contacted for future studies. The second phase of SELCoH (hereafter SELCoH-II) is a coordinated follow up of participants that participated in the SELCoHI who have agreed to be followed up. This study is also shared with the study entitled, ‘An Health Disparities Study of Discrimination & Disparities in Health & Health Service Use in the UK and US (Health Disparities study) for which the UK sample is drawn from SELCoH I. Thus SELCoHII aimed to update the locally relevant prevalence estimates and to investigate the influence of deleterious experiences across different demographic groups. Recruitment of SELCoH study participants began by sending a letter describing the study. This was sent two weeks in advance of interviewers visiting a household. During each household visit, interviewers attempted contact with a resident. Where contact was achieved, potential participants were given study information, reminded that their continued engagement was voluntary and, where possible, scheduled for an in-home interview. A maximum of four contact attempts (inclusive of any messages and/or home visits) were permitted per eligible individual. Closely supervised, trained interviewers conducted face-to-face interviews with computer assisted interview schedules. The survey questionnaire collected information on the following topics: (1) demographics; (2) migration; (3) socioeconomic status (SES); (4) ethnic identity (5)work attitude and experience (6) psychosocial factors (e.g., social support); (7) neighbourhood characteristics; (8) social adversity; (9) health behaviours; (10) physical and mental health status; (11) treatment and health service use; (12) access to technology; (13) the experience of unfair treatment and discrimination; (14) coping methods; (15) wellbeing. Translators employed by the SLAM NHS Trust were used in interviews with non-English speaking adults upon request. Participants were able to end the interview at any time and compensated for their time. We also provided an option to do a telephone interview for participants who moved out of London. References 1. Jenkins R, Bebbington P, Brugha T, Farrell M, Gill B, Lewis G, Meltzer H, Petticrew M: The National Psychiatric Morbidity surveys of Great Britain-strategy and methods. Psychological Medicine 1997, 27(4): 765-774. 2. Hatch SL, Frissa S, Verdecchia M, Stewart R, Fear NT, Reichenberg A, Morgan C, Kankulu B, Clark J, Gazard B, Medcalf R, the SELCoH study team, Hotopf M: Identifying socio-demographic and socioeconomic determinants of health inequalities in a diverse London community: the South East London Community Health (SELCoH) study. BMC Public Health (2011) 11:861