The time-dependent county attributes include a socioeconomic status (SES) index and seven county-level SES attributes that were used to construct the index. The attributes and the index are estimated at various time points using data obtained from the 1990 and 2000 U.S. Decennial Census long form survey, and a series of American Community Survey (ACS) 5-year estimates from 2006 to 2021. At each time point, a SES index is constructed from these attributes using a factor analysis (Yu et al. 2014). The attributes and the index are then linked to cancer cases/deaths at the county level by matching the survey data year and diagnosis/death year. Thus, for any of the seven attributes and index, cancer cases/deaths in the same county may have different values for different years. The mapping of the SES attributes/index and diagnosis or death year are shown in Table 1.
|Years||Data Source||Geographic Definition||Counties|
|1990-1993||1990 Census||1990||All counties|
|1994-1995||1990 Census||1990||All counties except combined Aleutians East Borough and Aleutians West Borough, Alaska, combined Dillingham Census Area and Lake and Peninsula Borough, Alaska , combined Skagway-Hoonan-Angoon Census Area and Yakutat City and Borough, Alaska and combined La Paz County and Yuma County, Arizona|
|1994-1995||2000 Census||2000||Aleutians East Borough, Alaska (02013)
Aleutians West Borough, Alaska (20016)
Dillingham Census Area, Alaska (02070)
Lake and Peninsula Borough, Alaska (02164)
Skagway-Hoonan-Angoon Census Area, Alaska (02232)
Yakutat City and Borough, Alaska (02282)
La Paz County, Arizona (04012)
Yuma County, Arizona (04027)
|1996-2001||2000 Census||2000||All counties|
|2002-2005||2000 Census||2000||All counties except Adams County, Boulder County, Jefferson County and Weld County, Colorado|
|2002-2005||ACS 2006-10||2010||Adams County, Colorado (08001)
Boulder County, Colorado (08013)
Broomfield County, Colorado (08014)
Jefferson County, Colorado (08059)
Weld County, Colorado (08123)
|2006-2008||ACS 2006-10||2010||All counties|
|2009||ACS 2007-11||2010||All counties|
|2010||ACS 2008-12||2010||All counties|
|2011||ACS 2009-13||2010||All counties|
|2012||ACS 2010-14||2010||All counties|
|2013||ACS 2011-15||2010||All counties|
|2014||ACS 2012-16||2010||All counties|
|2015||ACS 2013-17||2010||All counties|
|2016||ACS 2014-18||2010||All counties|
|2017||ACS 2015-19||2010||All counties|
|2018||ACS 2016-20||2020||Chugach Census Area (FIPS Code:02063) and Copper River Census Area (02066) combined to create Valdez-Cordova Census Area (02261)|
|2019-2021||ACS 2017-21||2020||Chugach Census Area and Copper River Census Area combined to create Valdez-Cordova Census Area|
The selection of attributes for constructing the SES index is based on Yost et al. (2001). Below are the tables and formulas used to calculate the base variables used in constructing the SES score. The tables are from the 2017-2021 American Community Survey (ACS) 5 –year estimates. Similar tables were used from the 1990 and 2000 Census and the 2006-2010, 2007-2011, 2008-2012, 2009-2013, 2010-2014, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, and 2016-2020 ACS.
Median Household Income
Median household income is taken from table B19013: Median Household Income in the Past 12 Months (in 2021 inflation adjusted dollars). The inflation adjustment is different for each of the data sources (i.e., 2016-20 ACS median income is in 2020 inflation adjusted dollars). In addition to the median income from the original data source, median income is available for all time points adjusted to 2021 dollars. This is available as dollars and income groupings.
Median House Value
Median house value is taken from table B25077: Median Value (Dollars).
Median Gross Rent
Median gross rent is taken from table B25064: Median Gross Rent (Dollars)
Percent Below 150% Poverty
The percent below 150% of poverty line is calculated using table C17002: Ratio of Income to Poverty Level in the Past 12 Months. The formula for this is:
- Below 150% poverty: ((C17002e02 + C17002e03 + C17002e04 + C17002e05) / C1702e01) * 100
The education index is calculated using table B15002: Sex by Educational Attainment for the Population 25 Years and Over. The percent with less than high school graduate, high school only and more than high school are calculated, as follows:
- Less than HS grad: ((B15002e03 + ... + B15002e10 + B15002e20 + ... + B15002e27) / B15002e01) * 100
- HS Only: ((B15002e11+B15002e28)/B15002e01) * 100
- More than HS grad: ((B15002e12 + ... + B15002e18 + B15002e29 + ... + B15002e35) / B15002e01) * 100
Using the percentages calculated above, the education index is calculated as follows:
- Education Index: (Less than HS grad * 9) + (HS only *12) + (More than HS grad * 16)
The percent working class is calculated using table C24010: Sex by Occupation for the Civilian Employed Population 16 Years and Over. The formula for this is:
- Working Class: ((C24010e20 + C24010e24 + C24010e25 + C24010e26 + C24010e27 + C24010e30 + C24010e34 + C24010e56 + C24010e60 + C24010e61 + C24010e62 + C24010e63 + C24010e66 + C24010e70)) / C24010e01) * 100
The percent of persons ages 16 and over who are unemployed is calculated using table B23025: Employment Status for the Population 16 Years and Over. The percent unemployed is calculated for civilians in the labor force. Persons in the armed forces or not in the labor force are not included in the calculation. The formula used is:
- Unemployed: (B23025e05 / B23025e03) * 100
Rural-Urban Continuum Codes
Rural-Urban Continuum Codes were developed by the United States Department of Agriculture (USDA).
Rural-Urban Continuum Codes form a classification scheme that distinguishes metropolitan (metro) counties by the population size of their metro area, and nonmetropolitan (nonmetro) counties by degree of urbanization and adjacency to a metro area or areas. For more information about using Rural-Urban Continuum Codes, go to Rural-Urban Continuum Codes in SEER*Stat.
Yost K, Perkins C, Cohen R, Morris C, Wright W (2001) Socioeconomic status and breast cancer incidence in California for different race/ethnic groups. Cancer Causes Control 12(8):703–711. doi:10.1023/a:1011240019516.
Yu M, Tatalovich Z, Gibson JT, Cronin KA. Using a composite index of socioeconomic status to investigate health disparities while protecting the confidentiality of cancer registry data. Cancer Causes & Control. 2014;25(1):81-92.