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Unemployment rate


Unemployment is associated with higher rates of self-reported poor health, long-term illnesses, higher incidence of risky health behaviors (e.g., alcoholism, smoking), and increased mortality. These negative health outcomes affect not only the unemployed persons but can extend to their families. Longer unemployment can be associated with higher odds of negative health effects. Various explanations have been proposed for the link between poor health and unemployment; for example, economic deprivation that results in reduced access to essential goods and services. Another explanation is that unemployment causes the loss of latent functions (e.g., social contact, social status, time structure, and personal identity) that can result in stigma, isolation, and loss of self-worth. The safety net available to the unemployed is weaker than in the past due to the deterioration of employment rights and a decrease in social support and welfare systems.
Studies at the county level found a positive association between higher unemployment and overall mortality and death due to cardiovascular disease and suicide; however, a negative relationship was detected with deaths due to motor-vehicle accidents. Individual level longitudinal studies showed that the unemployed had higher rates of poor physical health, suicides, mental health problems (e.g., depression, stress, anxiety), and greater use of healthcare services. Other studies found reduced access to healthcare services and higher likelihood to delay care among the unemployed.

The population in the labor force is the civilian non-institutionalized population 16 years and older who have jobs or are actively looking for jobs. Persons in the labor force are classified as unemployed if they do not have a job, are currently available for work, and have actively looked for work in the previous month (for instance, attending interviews, sending out resumes, or filling out applications). People that do not have a job and are not looking for one are considered not to be in the labor force. Women, youth (16 to 24 years), the least educated, and ethnic minorities are more likely to be unemployed.


Note to LHDs in California: The Healthy Community Indicators project has already downloaded and compiled these data; see Appendix C. The screen shots are for regions outside of California.

To track unemployment, two data sources are needed. One is table DP03 from the American Community Survey at the Census tract level and the other are Local Area Unemployment Statistics (LAUS) from the Bureau of Labor Statistics. For a detailed explanation of how to access American Community Survey data, see Appendix B. The ACS data can identify unemployment rates in Census tracts and provide race and ethnic stratification in those tracts. The LAUS can identify trends in counties and cities with 25,000 inhabitants and greater. For steps on how to download and map data from the American Community Survey, see Appendix B. Figure 17 shows the percent of resident actively seeking work who are unemployed at the Census tract level. Stratification by race and ethnicity is also available from the five-year ACS files. Tracts in red should be considered for further health department assessment and intervention.

Figure 17: Unemployment Rate, BARHII Region, 2006–2010

Figure 17: Unemployment Rate, BARHII Region, 2006–2010

Trends are available for states, counties, and localities with 25,000 people or greater from the LAUS dataset. LAUS can monitor overall trends in unemployment in cities and towns of 25,000 people and above. Data for Oakland, California was obtained with these steps:

How To Analyze Rates of Unemployment

STEP 01. Go to http://www.bls.gov/lau. On the home page menu, click on “Data Tools.”


STEP 02. On the Data Tools page, click “Unemployment.”


STEP 03. Click on Local Area Unemployment Statistics (LAUS), “Multi screen data search.”


STEP 04. Select “California”, click “Next form.”


STEP 05. Select “Cities and Towns above 25,000 Population,” click “Next form.” County-level data can be acquired by selecting “Counties and Equivalents” and following the subsequent steps.


STEP 06. Select all the cities in the list, click “Next form.”


STEP 07. Select “unemployment rate,” “unemployment,” and “labor force,” click “Next form.”


STEP 08. Check the box for “Not Seasonally Adjusted,” click “Next form.”


STEP 09. Click “Retrieve data.”

STEP 10. This step creates a printout of all localities in California with 25,000 people or greater. Scroll down to the city of your choice, Oakland in this example. These data can be pasted in a spreadsheet program. The screenshot below shows HTML, but a CSV file can be generated by clicking “More Formatting Options.”

STEP 10A. (optional) These data are also available as a CSV file, which can be more easily imported into a new spreadsheet. If a CSV file of LAUS is downloaded, a crosswalk file is needed to match the record ID number in the LAUS file with a city name located in the crosswalk. Download the crosswalk and the code list files located at http://www.bls.gov/lau/crosswalk.xlsx. This file matches the ID number with a city name. Additional manipulation is needed to merge the two datasets.

STEP 11. Identify the cities in your county with the highest rate of unemployment and construct a trend chart like the one below. Data for Alameda County, which contains Oakland, can be acquired in the same way as for Oakland. To do so, begin at step 5 and repeat steps 6 through 10.

Sample interpretation: From 2004–2013, trends in unemployment for the city of Oakland mirrored those of Alameda County. Both Oakland and Alameda County experienced significant increases in unemployment due to the financial crisis in 2008 and the subsequent recession, but Oakland’s unemployment rate was higher. In recent years, unemployment has been declining in both Alameda County and in the City of Oakland.

Figure 18: Unemployment rate, Alameda County and Oakland, 2004-2013



Emergency Medical Services Corps Program
Alameda County Public Health Department

The Emergency Medial Services (EMS) Corps is a highly selective, rigorous academy that trains aspiring emergency medical professionals who are from the community and ready to serve. It is a paid (stipend) program whose mission is to increase the number of underrepresented emergency medical technicians through youth development, mentorship, and job training. Program elements include EMT training, transformative mentoring/male development, life coaching, case management, mentorship, mental health and self-care reform, and academic tutoring.

The primary purpose of Alameda County EMS, a division of Health Care Services Agency, is to provide oversight and administration of medical 911 responses throughout the county. Parts of their responsibilities are education and community programs. There was a growing concern with seeing a disproportional representation of minorities in the pool of EMTs and firefighters serving their communities. After uncovering approaches in finding pathways to emergency medical careers, there was a conscience effort to provide training for young minority adults, including offering trainings through a local juvenile hall facility. In addition, Alameda County EMS leveraged their contracts with local 911 responder companies to make the hiring of EMS Corps graduates a priority. This training and its job connections allows them to serve their communities and become competent contributors and members of the changing and growing pool of first responders.

Building Economic Security Today (BEST)
Contra Costa County Public Health Department

Contra Costa inserted a program into their Women, Infants, & Children (WIC) services to help WIC recipients understand the income tax process and apply for the Earned Income Tax Credit. Agency leaders understood that poverty is a major determinant of poor health, and that by helping support asset development and economic sustainability, the health department can advance the health of women and children in their community. So far, over 6,000 women have participated, and participants report feeling more confident about handling money and have an improved understanding of the impact of money on health.

Bambra C, Eikemo TA. 2009. Welfare State Regimes, Unemployment and Health: A Comparative Study of the Relationship between Unemployment and Self-Reported Health in 23 European Countries. Journal of Epidemiology and Community Health 63:92–98.

Janlert U, Hammarström A. 2009. Which Theory is Best? Explanatory Models of the Relationship between Unemployment and Health. BMC Public Health 9:235.

Bambra C. 2010. Yesterday Once More? Unemployment and Health in the 21st Century. Journal of Epidemiology and Community Health 64:213-215.

Bureau of Labor Statistics. 2014. Labor Force Statistics from the Current Population Survey. http://www.bls.gov/cps/cps_htgm.htm. Accessed June 2014.

Employment Conditions Knowledge Network (EMCONET). 2007. Employment Conditions and Health Inequalities. Accessed June 2014.

Jin R, Chandrakant PS, Tomislav JS. 1995. The Impact of Unemployment on Health: A Review of the Evidence. Canadian Medical Association Journal 153(5):529-540.

Mossakowski K. 2009. The Influence of Past Unemployment Duration on Symptoms of Depression among Young Women and Men in the United States. American Journal of Public Health 99(10):1826-1832.

Pharr JR, Moonie S, Bungum T. 2012. The Impact of Unemployment on Mental and Physical Health, Access to Health Care and Health Risk Behaviors. ISRN Public Health Volume 2012, Article ID 483432, 7 pages.