U.S. Census Data Calculations
(1970, 1980, 1990, 2000)

Data Processing (1970, 1980, 1990, and 2000 Censuses)

A) 1970 Census: Time Series Demographic Statistics

The Block Group Census 1970 data were provided by the Center for Electronic Records (NWME) of The National Archives at College Park as special fifth-count tallies in FORTRAN® format with a record length of 1, 920 characters and approximately 330, 000 logical records for the United States. These tallies were created from the assembled,  edited 20,  15,  and 5% sample portions of the 1970 Census of Population and Housing. The Census Areas available were Enumeration Districts (ED’s),  or Block Groups (BG’s) Tracts and/or Minor Civil Divisions (MCD’s) or Census County Divisions (CCD’s).

The following footnotes appear in the description of variables (documentation).

Geo-referenced population points 1970 estimates were reported by geographic county sub-divisions known as Census Block Group and/or Enumeration Districts by the U.S. Bureau of the Census,  Geographic Division,  Geo-Spatial Research and Standards staff. The points were imported to ArcView®. Estimates were assigned watershed attributes through a GIS overlay operation with NOAA’s Coastal Assessment Framework (CAF). The demographic variables data were then summarized by NOAA’s unique code,  USGS 8-digit Hydrologic Cataloging Unit (HUC) code and Watershed (EDA,  CDA,  FDA) codes. Unique in the CAF is the intersection area of an 8-digit Cataloging Unit and Estuarine Drainage Areas. County level estimates were obtained by summarizing the demographic variables by the existent 5-digit FIPS code associated to each Census Block Group point data. FIPS in this document refers to the 2-digit state FIPS code plus the 3-digit county FIPS code. Flag variables were created to inform the user that a number of points fall either outside of the county the point is supposed to be or on water. A more detailed processing steps follows:

Data Files

1. 1970 MEDlist with coordinates obtained from CD-ROM provided by Geospatial Research and Standards Staff,  Geography Division,  Bureau of the Census. Total of nine space delimited files. This will be called the CENSUS file in this documentation.
2. 1970 Census of Population and Housing Data provided by National Archive. Total of fifty one ASCII files compiled by SPO. This will be called the NOAA file in this documentation.

Processing of CENSUS file:

1.    Obtaining the CENSUS file

• Total number of original records: 297, 146
• Deleting records with no Tract BG/ED: 39, 804
• Adjusted record number: 257, 342
• The block group data are split in urban and non-urban areas.   Since the NOAA file data are by block group it was necessary to aggregate the CENSUS file to a block group level in order to perform a merge.
• Summarized by CENS70ID: 250, 494 records (file to be merged with NOAA file)
  CENS70ID is a 21 character unique record id obtained as follows:
  
  CENS70ID = state70 + cnty70 + place + tract_b + tract_s + bg + ed_b + ed_s

2. Records with population count and missing lat/lon coordinates:

3. Quality Control on lat/lon data

The CENSUS file was plotted in NOAA’s 1990 county file. An assessment variable called "LL_FLAG" was created for assessing lat/lon data. The codes in the LL_FLAG are:

L   = Correct FIPS,  plots on land (213, 848 records)

W = Correct FIPS,  plots on water (1, 186 records)

5   = Incorrect FIPS,  but within 5 miles of correct FIPS (1, 097 records - considered a good coordinate for purpose of assigning NOAA watershed codes)

O  = Alaska and Hawaii points,  outside of CAF (1, 629 records)

A  = Considered bad lat/lon data and entered to missing in this file to be later adjusted (378 cases). When lat/lon coordinates are missing,  lat/long coordinates are entered based on a track average coordinate or FIPS average coordinate. The original data of these 378 cases were kept in a file called "c70adj.txt".

C = FIPS codes are changed because the 1970 FIPS do not exist in 1990 FIPS coverage (102 records). The FIPS changed are:

29193 changed to 29186
36099 changed to 36069
51123 changed to 51800
46131 changed to 46071

The original data of these 102 cases were kept in a file called "c70cfip.txt"

P = Points that have correct lat/lon data. However,  these points fall in counties that were split as shown in the 1990 coverage (31 records). These FIPS codes are changed as follows:

35061 changed to 35006
04027 changed to 04012

The original data of these 31cases are in a file called "c70cpnt.txt".

Processing of NOAA file:

1. The original file contains 286, 150 records. A census id variable (CENS70ID) was also created to merge this NOAA file with the CENSUS file. The file was summarized by the CENS70ID variable obtaining a file with 262, 243 records. This file contained missing codes for block group and enumeration district records.  These records were deleted and obtained a file with 225,068 records.  It was checked that by deleting records with block group and enumeration missing codes, the number of people aggregated to counties was the same or very close to number of people by county using the "med1970" file (CENSUS file).  As with the CENSUS file,  LL_FLAG codes were obtained. The merged file (225,068 records) called from now on "CENSUS70 file" contains the following number of records by the LL_FLAG:

L  = 221,318  records
W =     1,186 records
5  =      1,097 records
C =           97 records
O =      1,339 records
P =            31 records

2. Cases with missing lat/lon data were assigned coordinates by making use of a tract average coordinate. If an average tract coordinate could not be obtained,  a FIPS average coordinate was used to make the lat/lon assignment. A variable called "LLSRCE" was created to keep track of these assignments. The final file contains the following LLSRCE codes:

C = lat/lon data from the CENSUS file (216, 330 records)
T = lat/lon data from a tract average coordinate (8,588 records)
F = lat/lon data from a FIPS average coordinate (150 records)

3. The CENSUS70 file was then tagged to NOAA’s Coastal Assessment Framework watersheds and USGS 8-digit Cataloging Units.

4.    To obtain a Time Series Population and Housing file (1970,   1980, 1990, and 2000),  the following variables that are common to the 1980, 1990, and 2000 censuses were obtained from the CENSUS70 file (for a complete listing of all variables in the Original CENSUS 1970 click here).

urban, nonurban and total population (count of persons)

• urban
  c70urbn = (c70v0027)
• rural
  c70nurbn = sum(c70v0028,  c70v0029)
• rural farm
  c70rnfar = round(c70v0028)
• rural non-farm
  c70rfarm = round(c70v0029)
• total population
  c70popul = sum(c70urbn, c70nurbn)

race (count of persons)

• white,  black and other
  c70white = (c70v0030)
  c70black = (c70v0031)
  c70other = (sum(c70v0032,  c70v0033, c70v0034, c70v0035,   c70v0036))

language = (count of persons 5 years and over)

• english,  spanish, other languages
  c70engli =  (c70v0040)
  c70spani =  (c70v0045)
  c70hloth = (sum(c70v0041, c70v0042, c70v0043, c70v0044, c70v0046, c70v0047))

age (count of persons)

sex  (count of persons)

• c70male = (sum(c70v0062, c70v0063, c70v0064, c70v0065, c70v0066, c70v0067, c70v0068, c70v0069, c70v0070, c70v0071, c70v0072, c70v0073, c70v0074, c70v0075, c70v0076, c70v0077, c70v0078, c70v0079, c70v0080, c70v0081, c70v0082, c70v0083, c70v0084))
• c70fema = (sum(c70v0085, c70v0086, c70v0087, c70v0088, c70v0089, c70v0090, c70v0091, c70v0092, c70v0093, c70v0094, c70v0095, c70v0096, c70v0097, c70v0098, c70v0099, c70v0100, c70v0101, c70v0102, c70v0103, c70v0104, c70v0105, c70v0106, c70v0107)

family income (count of families)

• family income less than $ 9, 999
  c70fi1 = (sum(c70v0481, c70v0482, c70v0483, c70v0484, c70v0485, c70v0486,  c70v0487,  c70v0488,  c70v0489,  c70v0490))
• family income $ 10, 000 to $ 14, 999
  c70fi2 = (sum(c70v0491,  c70v0492))
• family income $ 15, 000 to $ 24, 999
  c70fi3 = (c70v0493)
• family income $ 25, 000 to $ 49, 999
  c70fi4 = (c70v0494)
• family income $ 50, 000 and over
  c70fi5 = (c70v0495)

school enrollment (count of persons 3 - 34 yr. enrolled in school)

education attainment (count of persons 25 yr. old and over)

occupation (count of employed persons 16 yr. old and over)

• executive-administrative-managerial
  (farmers and farm managers,  managers,  officials & proprietors except farm)
  c70occu2 = (sum(c70v0461, c70v0462))

industry (count of employed persons 16 yr. old and over)

poverty status (count of persons for whom poverty status is determined)

c70above = (sum(c70v0549, c70v0550))
c70below = (sum(c70v0551, c70v0552))

nativity (count of persons)

• natives
  c70nativ = sum(c70v0037, c70v0038)
• foreign
  c70forei = (c70v0039)

household relationship (count of persons)

• in family household
  c70fhous = sum(c70v0246, c70v0247, c70v0248, c70v0249)
• in group quarters
  c70gquar = sum(c70v0250, c70v0251)

family type (count of families)

• all families
  c70allfa = (c70v0270)
• families with female head
  c70fawfh = (c70v0273)

population 14 years old and over by sex
(count of persons 14 years old and over)

• male
  c70m14yr = sum(c70v0294, c70v0295, c70v0296, c70v0297, c70v0298)
• female
  c70f14yr = sum(c70v0299, c70v0300, c70v0301, c70v0302, c70v0303)

population 5 years old and over by residence
(count of persons 5 years old and over)

• same house
  c70shous = (c70v0374)
• different house
  c70dhous = sum(c70v0375, c70v0376, c70v0377, c70v0378, c70v0379, c70v0380)
• abroad
  c70abroa = (sum(c70v0381, c70v0382)

labor force by sex (count of persons 16yrs old and over)

• male in labor force (armed forces, employed, unemployed, inmate of institution)
  c70mlfor = sum(c70v0412, c70v0413, c70v0414, c70v0415)
• male other not in labor force
  c70mnlfo = sum(c70v0416, c70v0417)
• female in labor force (armed forces, employed, unemployed, inmate of institution)
  c70flfor = sum(c70v0418, c70v0419, c70v0420, c70v0421)
• female other not in labor force
  c70fnlfo = sum(c70v0422, c70v0423)

families with female head by poverty status
(count of families with female head)

• above poverty level
  c70fhabo = sum(c70v0539, c70v0540)
• below poverty level
  c70fhbel = sum(c70v0541, c70v0542)

families by poverty status (count of families)

• families above poverty level
  c70fabov = sum(c70v0543, c70v0544)
• families below poverty level
  c70fbelo = sum(c70v0545, c70v0546)

tenure (count of occupied housing units)

• owner occupied
  c70owner = (c70v0568)
• renter occupied
  c70rente = (c70v0569)

tenure by units of structure (count of housing units)

• In 1 unit structure
  c70tstr1 = (c70v0703)
• In 2 unit structure
  c70tstr2 = (c70v0704)
• In 3-4 unit structure
  c70tstr3 = (c70v0705)
• In 5 or more unit structure
  c70tstr4 = sum(c70v0706,c70v0707)
• mobile homes, trailers, other
  c70tstr5 = (c70v0708)

gross rent
(count of renter occupied units by monthly gross rent)

• less than $ 100
  c70gren1 = sum(c70v0682, c70v0683, c70v0684, c70v0685)
• $ 100 to $ 199
  c70gren2 = sum(c70v0686, c70v0687)
• $ 200 to $ 299
  c70gren3 = sum(c70v0688, c70v0689)
• $ 300 or more
  c70gren4 = (c70v0690)

telephone available and tenure (count of occupied housing units)

• owner occupied, telephone available
  c70tele1 = (c70v0693)
• owner occupied, telephone not available
  c70tele2 = (c70v0694)
• renter occupied, telephone available
  c70tele3 = (c70v0695)
• owner occupied, telephone not available
  c70tele4 = (c70v0696)

vehicles available (count of occupied housing units with vehicle available)

• 1 automobile
  c70auto1 = (c70v0782)
• 2 automobiles
  c70auto2 = (c70v0783)
• 3 or more automobiles
  c70auto3 = (c70v0784)

heating fuel (count of occupied housing units)

• utility gas
  c70heat1 = round(c70v0889)
• bottled, tank or LP gas
  c70heat2 = (c70v0890)
• electricity
  c70heat3 = (c70v0891)
• other
  c70heat4 = (sum(c70v0892, c70v0893, c70v0894, c70v0895)
• no fuel used
  c70heat5 = (c70v0896)
  

5.    Several data variables in the NOAA file contained non-disclosure information flagged as "-1". In order to obtain aggregated data by NOAA’s different spatial units,  it was required to fill in the missing values. The approach to do this was to obtain a percentage of the variable in question in regard to the total in the county. This percentage was used to prorate the population at the block group level with the following SAS program:

if c70white = -1 or c70black = -1 or c70other = -1 then do;
   c70white = round(c70popul*pwhite/100);
   c70black = round(c70popul* pblack/100);
   c70other = round(c70popul *pother/100);
end;

if c70engli = -1 or c70spani = -1 or c70hloth = -1 then do;
   c70engli = round(c70popul*pengli/100);
   c70spani = round(c70popul*pspani/100);
   c70hloth = round(c70popul*phloth/100);
end;

if c70age1 = -1 or c70age2 = -1 or c70age3 = -1
or c70age4 = -1 or c70age5 = -1 or c70age6 = -1
or c70age7 = -1 or c70age8 = -1 or c70age9 = -1
or c70age10 = -1 or c70age11 = -1 or c70age12 = -1
or c70age13 = -1 or c70age14 = -1 or c70age15 = -1
or c70age16 = -1 or c70age17 = -1 or c70age18 = -1
or c70age19 = -1 or c70age20 = -1 or c70age21 = -1
or c70age22 = -1 or c70age23 = -1 then do;
   c70age1 = round(c70popul* page1 /100);
   c70age2 = round(c70popul* page2 /100);
   c70age3 = round(c70popul* page3 /100);
   c70age4 = round(c70popul* page4 /100);
   c70age5 = round(c70popul* page5 /100);
   c70age6 = round(c70popul* page6 /100);
   c70age7 = round(c70popul* page7 /100);
   c70age8 = round(c70popul* page8 /100);
   c70age9 = round(c70popul* page9 /100);
   c70age10 = round(c70popul* page10/100);
   c70age11 = round(c70popul* page11/100);
   c70age12 = round(c70popul* page12/100);
   c70age13 = round(c70popul* page13/100);
   c70age14 = round(c70popul* page14/100);
   c70age15 = round(c70popul* page15/100);
   c70age16 = round(c70popul* page16/100);
   c70age17 = round(c70popul* page17/100);
   c70age18 = round(c70popul* page18/100);
   c70age19 = round(c70popul* page19/100);
   c70age20 = round(c70popul* page20/100);
   c70age21 = round(c70popul* page21/100);
   c70age22 = round(c70popul* page22/100);
   c70age23 = round(c70popul* page23/100);
end;

if c70male = -1 or c70fema = -1 then do;
   c70male = round(c70popul* pmale /100);
   c70fema = round(c70popul* pfema /100);
end;

if c70above = -1 then do;
   c70above = round(c70above*pabove / 100);
end;

if c70below = -1 then do;
   c70below = round(c70below*pbelow / 100);
end;

if c70forei = -1 then do;
c70forei = round(c70popul * pforei/100);
end;

if c70fhous = -1 then do;
c70fhous = round(c70popul * pfhous/100);
end;

if c70gquar = -1 then do;
c70gquar = round(c70popul * pgquar/100);
end;

where:

c70popul = c70urbn + c70nurbn

pwhite,  pblack,  pother,  pengli,  pspani,  photh,   page1-page23, pmale,  pfema, pabove, and pbelow are percentages of variables containing non-disclosure information.

NOTE: Because of rounding, numbers for cases above might not add perfectly to total counts.

For all other cases below of non-disclosure information where the "universe" was not persons, values were entered as missing:

if c70fi1 = -1 then c70fi1 = .;
if c70fi2 = -1 then c70fi2 = .;
if c70fi3 = -1 then c70fi3 = .;
if c70fi4 = -1 then c70fi4 = .;
if c70fi5 = -1 then c70fi5 = .;
if c70fi6 = -1 then c70fi6 = .;
if c70ncoll = -1 then c70ncoll = .;
if c70colle = -1 then c70colle = .;
if c70educ1 = -1 then c70educ1 = .;
if c70educ2 = -1 then c70educ2 = .;
if c70educ3 = -1 then c70educ3 = .;
if c70educ4 = -1 then c70educ4 = .;
if c70occu1 = -1 then c70occu1 = .;
if c70occu2 = -1 then c70occu2 = .;
if c70occu3 = -1 then c70occu3 = .;
if c70occu4 = -1 then c70occu4 = .;
if c70occu5 = -1 then c70occu5 = .;
if c70occu6 = -1 then c70occu6 = .;
if c70occu7 = -1 then c70occu7 = .;
if c70occu8 = -1 then c70occu8 = .;
if c70occu9 = -1 then c70occu9 = .;
if c70indu1 = -1 then c70indu1 = .;
if c70indu2 = -1 then c70indu2 = .;
if c70indu3 = -1 then c70indu3 = .;
if c70indu4 = -1 then c70indu4 = .;
if c70indu5 = -1 then c70indu5 = .;
if c70indu6 = -1 then c70indu6 = .;
if c70indu7 = -1 then c70indu7 = .;
if c70indu8 = -1 then c70indu8 = .;
if c70indu9 = -1 then c70indu9 = .;
if c70ind10 = -1 then c70ind10 = .;
if c70ind11 = -1 then c70ind11 = .;
if c70allfa = -1 then c70allfa = .;
if c70fawfh = -1 then c70fawfh = .;
if c70m14yr = -1 then c70m14yr = .;
if c70f14yr = -1 then c70f14yr = .;
if c70shous = -1 then c70shous = .;
if c70dhous = -1 then c70dhous = .;
if c70abroa = -1 then c70abroa = .;
if c70mlfor = -1 then c70mlfor = .;
if c70mnlfo = -1 then c70mnlfo = .;
if c70flfor = -1 then c70flfor = .;
if c70fnlfo = -1 then c70fnlfo = .;
if c70inco1 = -1 then c70inco1 = .;
if c70inco2 = -1 then c70inco2 = .;
if c70inco3 = -1 then c70inco3 = .;
if c70inco4 = -1 then c70inco4 = .;
if c70inco5 = -1 then c70inco5 = .;
if c70inco6 = -1 then c70inco6 = .;
if c70fhabo = -1 then c70fhabo = .;
if c70fhbel = -1 then c70fhbel = .;
if c70fabov = -1 then c70fabov = .;
if c70fbelo = -1 then c70fbelo = .;
if c70owner = -1 then c70owner = .;
if c70rente = -1 then c70rente = .;
if c70tstr1 = -1 then c70tstr1 = .;
if c70tstr2 = -1 then c70tstr2 = .;
if c70tstr3 = -1 then c70tstr3 = .;
if c70tstr4 = -1 then c70tstr4 = .;
if c70tstr5 = -1 then c70tstr5 = .;
if c70gren1 = -1 then c70gren1 = .;
if c70gren2 = -1 then c70gren2 = .;
if c70gren3 = -1 then c70gren3 = .;
if c70gren4 = -1 then c70gren4 = .;
if c70tele1 = -1 then c70tele1 = .;
if c70tele2 = -1 then c70tele2 = .;
if c70tele3 = -1 then c70tele3 = .;
if c70tele4 = -1 then c70tele4 = .;
if c70auto1 = -1 then c70auto1 = .;
if c70auto2 = -1 then c70auto2 = .;
if c70auto3 = -1 then c70auto3 = .;
if c70heat1 = -1 then c70heat1 = .;
if c70heat2 = -1 then c70heat2 = .;
if c70heat3 = -1 then c70heat3 = .;
if c70heat4 = -1 then c70heat4 = .;
if c70heat5 = -1 then c70heat5 = .;

Aggregated population data by county was compared from the two sources, NOAA file (population and housing data) and Census File (georeference file). The result from this county comparison is shown in the table below:

Table 1. Comparison of County Population Data from Sources: Census Geographic Division and USGS

where:

pop70 = 1970 county population (source: georeference file from Geospatial Research and Standards staff, Geography Division, at US bureau of the Census)

c70popul = 1970 county population (source: NOAA file from Center for Electronic Records, The National Archives at College Park)

DIFF = pop70 / c70popul

We can conclude that in general county population counts from the two sources,  Census file and NOAA file, agreed well (see table 1 above).

B) 1980 Census: Time Series Demographic Statistics

1. The Block Group Census 1980 data were provided by the U.S. Bureau of the Census,  Geographic Division,  Geo-Spatial Research and Standards staff as ASCII comma delimited files and then imported into the Statistical Analysis System (SAS) software by Special Projects staff for further processing and analysis.

Geo-referenced population points 1980 estimates were reported by Census Block Group and/or Enumeration Districts. The points were imported to MAPINFO® 4.5 for quality control purposes and watershed assignments. Estimates were assigned watershed attributes through a GIS overlay operation with NOAA’s Coastal Assessment Framework (CAF). The demographic variables data were then summarized by NOAA’s unique code,  USGS 8-digit Hydrologic Cataloging Unit (HUC) code and Watershed (EDA,  CDA,  FDA) codes. Unique in the CAF is the intersection area of an 8-digit Cataloging Unit and Estuarine areas. County level estimates were obtained by summarizing the demographic variables by the existent 5-digit FIPS code associated to each Census Block Group point data. Flag variables were created to inform the user that a number of points fall either outside of the county the point is supposed to be or on water.

All the block level state files were merged into one to obtain the CENSUS80 file. A unique 22 digit record ID (cens80id) was obtained by concatenating the following variables: state,  county,  place,   tractbna,  bg,  and ed_code, 

2. Quality Control on lat/lon data
As with the 1970 census file, using the same methodology, the 1980 Census file was subjected to a quality control performed on lat/lon data.

The CENSUS file was plotted in NOAA’s 1990 county file. An assessment variable called "LL_FLAG" was created for assessing lat/lon data. The codes in the LL_FLAG are:

L   = Correct FIPS,  plots on land  (282,194 records)

W = Correct FIPS,  plots on water (1,212 records)

5   = Incorrect FIPS,  but within 5 miles of correct FIPS (considered a good coordinate for purpose of assigning NOAA watershed codes) (319 records)

O  = Alaska and Hawaii points,  outside of CAF (1,874 records)

S = Correct State (for State Summary Level).

A  = Considered bad lat/lon data and entered to missing in this file to be later adjusted (7 records). The adjusted lat/lon coordinates (ll_flag=A) used the coordinates of the point having the largest population in the correct FIPS. The original coordinates of the adjusted points are:

cens80id  /  latitude  / longitude

0400701450000000000486 / 33.2128 / 111.1668
5102399990405003000000 / 36.5293 / 78.0551
5115700009901001000000 / 38.4280 / 78.7329
5119199990103001000000 / 36.4752 / 82.4304
5151000252002011000000 / 38.6412 / 77.3495
5151000252018019000000 / 38.6383 / 77.2943
5171008750005004000000 / 37.2858 / 79.9307

The file was then tagged to NOAA’s Coastal Assessment Framework to obtain watershed codes for data aggregation purposes.

3.    To obtain a Time Series Population and Housing file (1970,   1980, 1990, and 2000),  the following variables that are common to the 1970, 1990, and 2000 censuses were obtained from the CENSUS80 file (for a listing of most of all variables in the Original CENSUS 1980 click here).

urban, nonurban and total population (count of persons)

• urban
  c80urbn = (urban)
• rural
  c80nurbn = (rural)
• rural farm
  c80rfarm = (p008farm)
• rural non-farm
  c80rnfar = (p008nonf)
• total population
  c80popul = sum(c80urbn, c80nurbn)

race (count of persons)

• white,  black and other
  c80white = (white)
  c80black = (black)
  c80other=sum(a_indian, eskimo, aleut, japanese, chinese, filipino, korean, asindian, viet, hawiian, guamian, samoan, oa_or_pi,  spanish, unknown)

language (count of persons 5 years and over)

• english,  spanish,  other languages
  c80engli =  sum(eng5_17y, en18plus)
  c80spani =  sum(sew5_17y, sen5_17y, sew5_18p, sen5_18p)
  c80hloth = sum(oew5_17y, oen5_17y, oew5_18p, oen5_18p)

age (count of persons)

• persons under 2 years
  c80age1 = sum(t_lt_1yr, t_1_2yr)
• persons 3 to 4 years
  c80age2 = (t_3_4yr)
• persons 5 years
  c80age3 = (t_5yr)
• persons 6 years
  c80age4 = (t_6yr)
• persons 7 to 9 years
  c80age5 = (t_7_9yr)
• persons 10 to 13 years
  c80age6 = (t10_13yr)
• persons 14 years
  c80age7 = (t_14yr)
• persons 15 years
  c80age8 = (t_15yr)
• persons 16 years
  c80age9 = (t_16yr)
• persons 17 years
  c80age10 = (t_17yr)
• persons 18 years
  c80age11 = (t_18yr)
• persons 19 years
  c80age12 = (t_19yr)
• persons 20 years
  c80age13 = (t_20yr)
• persons 21 years
  c80age14 = (t_21yr)
• persons 22 to 24 years
  c80age15 = (t22_24yr)
• persons 25 to 34 years
  c80age16 = (sum(t25_29yr, t30_34yr))
• persons 35 to 44 years
  c80age17 = (t35_44yr)
• persons 45 to 54 years
  c80age18 = (t45_54yr)
• persons 55 to 59 years
  c80age19 = (t55_59yr)
• persons 60 to 61 years
  c80age20 = (t60_61yr)
• persons 62 to 64 years
  c80age21 = (t62_64yr)
• persons 65 to 74 years
  c80age22 = (t65_74yr)
• persons 75 and over
  c80age23 = sum(t75_84yr, t_85plus)

sex (count of persons)

• c80male = sum(m_lt_1yr, m_1_2yr, m_3_4yr, m_5yr, m_6yr, m_7_9yr, m10_13yr, m_14yr, m_15yr, m_16yr, m_17yr, m_18yr, m_19yr, m_20yr, m_21yr, m22_24yr, m25_29yr, m30_34yr, m35_44yr, m45_54yr, m55_59yr, m60_61yr, m62_64yr, m65_74yr, m75_84yr, m_85plus)
• c80fema = sum(f_lt_1yr, f_1_2yr, f_3_4yr, f_5yr, f_6yr, f_7_9yr, f10_13yr, f_14yr, f_15yr, f_16yr, f_17yr, f_18yr, f_19yr, f_20yr, f_21yr, f22_24yr, f25_29yr, f30_34yr, f35_44yr, f45_54yr, f55_59yr, f60_61yr, f62_64yr, f65_74yr, f75_84yr, f_85plus)

family income (count of families)

* The total count of families for this variable does not equal the reported 1980 total number of families reported elsewhere in this project. *

• family income less than $ 9, 999
  c80fi1 = sum(fi_1, fi_2, fi_3,  fi_4)
• family income $ 10, 000 to $ 14, 999
  c80fi2 = sum(fi_5,  fi_6)
• family income $ 15, 000 to $ 24, 999
  c80fi3 = sum(fi_7, fi_8, fi_9, fi_10)
• family income $ 25, 000 to $ 49, 999
  c80fi4 = sum(fi_11, fi_12, fi_13, fi_14, fi_15)
• family income $ 50, 000 and over
  c80fi5 = sum(fi_16, fi_17)

school enrollment (count of persons 3 yr old and over enrolled in school)

• persons in no college (nursery,  kindergarten,   elementary and high school)
  c80ncoll = sum(se_nurse, se_k_e, se_hs)
• persons in college
  c80colle = (se_coll)

education attainment (count of persons 25 yr. old and over)

• less than 12th grade
  c80educ1 = (ea_1_3hs)
• high school graduate
  c80educ2 = (ea_4hs)
• college 1 to 3 years (some college,  associate degree)
  c80educ3 = (ea_1_3co)
• college 4 years or more (bachelors or graduate degree)
  c80educ4 = sum(ea_4co, ea_5pco)

occupation (count of employed persons 16 yr. old and over)

• professional,  technical and kindred workers
  (professional and specialty,  technicians and related support)
  c80occu1 = sum(occ_ps, occ_tech)
• executive-administrative-managerial
  (farmers and farm managers,  managers,  officials & proprietors except farm)
  c80occu2 = (occ_eam)
• clerical and kindred workers
  (administrative support including clerical)
  c80occu3 = (occ_admn)
• sales workers
  c80occu4 = (occ_sale)
• craftsmen,  foremen,  and kindred workers
  (precision production-craft-repair)
  c80occu5 = (occ_ppcr)
• operatives and kindred workers
  (machine operators-assemblers-inspectors)
  c80occu6 = (occ_moai)
• service workers including private household
  (private household service,  protective service,   other service)
  c80occu7 = sum(occ_priv, occ_prot, occ_othr)
• farm laborers and farm foremen
  (farming-forestry-fishing)
  c80occu8 = (occ_fff)
• laborers except farm and mine
  (transportation and material moving)
  c80occu9 = sum(occ_tmm, occ_hecl)

industry (count of employed persons 16 yr. old and over)

• construction
  c80indu1 = (ind_con)
• manufacturing of durable goods and non-durable goods
  c80indu2 = sum(ind_ndg, ind_dg)
• transportation
  c80indu3 = (ind_tran)
• communications and other public utilities
  c80indu4 = (ind_util)
• wholesale and retail trade
  c80indu5 = sum(ind_wt, ind_rt)
• finance,  insurance,  business,  and repair
  c80indu6 = sum(ind_fie, ind_brs)
• other professional and related services
  c80indu7 = sum(ind_ops, ind_hs, ind_pers)
• educational services
  c80indu8 = (ind_es)
• public administration
  c80indu9 = (ind_pa)
• other industries
  c80ind10 = (ind_ag)

poverty status (count of persons for whom poverty status is determined)

c80above = sum(pl15_64, pl65pls, plg15_64, plg65pls)
c80below = sum(bpl15_64, bpl65pls)

nativity (count of persons)

* These variables were obtained from the Geolytics CD due to problems with the accuracy of the data obtained from the Census Bureau. *

• natives
  c80nativ = sum(Nativity and Place of Birth: Born in State of Residence, Born is Different State, Born Abroad, at Sea, etc.)
• foreign
  c80forei = (Nativity and Place of Birth - Foreign Born)

household relationship (count of persons)

• in family household
  c80fhous = sum(p019fahs,p019fano,p019faot,p019fanr,p019noma,
  p019nofe,p019nonr)
• in group quarters
  c80gquar = sum(p019gpin,p019gpot)

family type (count of families)

• all families
  c80allfa = sum(p020tmch,p020tmno,p020tmac,p020tman,p020tfec,p020tfen,p020tnon)
• families with female head
  c80fawfh = sum(p020tfec,p020tfen)

population 14 years old and over by sex
(count of persons 14 years old and over)

• male
  c80m14yr = sum(p026masi,p026mams,p026mase,p026mswi,p026madi)
• female
  c80f14yr = sum(p026fesi,p026fems,p026fese,p026fewi,p026fedi)

population 5 years old and over by residence
(count of persons 5 years old and over)

• same house
  c80shous = (p034same)
• different house
  c80dhous = sum(p034saco,p034sast,p034dfne,p034dfnc,p034dfso,p034dfwe)
• abroad
  c80abroa = (p034dfab)

labor force by sex (count of persons 16yrs old and over)

• male in labor force (armed forces, employed, unemployed, inmate of institution)
  c80mlfor = sum(p055tmaf,p055tmce,p055tmcu)
• male other not in labor force
  c80mnlfo = (p055tmni)
• female in labor force (armed forces, employed, unemployed, inmate of institution)
  c80flfor = sum(p055tfaf,p055tfce,p055tfcu)
• female other not in labor force
  c80fnlfo = (p055tfni)

families with female head by poverty status
(count of families with female head)

• above poverty level
  c80fhabo = sum(p086tach,p086tab6,p086taa6,p086tano)
• below poverty level
  c80fhbel = sum(p086tbch,p086tbb6,p086tba6,p086tbno)

families by poverty status (count of families)

• families above poverty level
  c80fabov = sum(p086fach,p086fab6,p086faa6,p086fano)
• families below poverty level
  c80fbelo = sum(p086fbch,p086fbb6,p086fba6,p086fbno)

tenure (count of occupied housing units)

• owner occupied
  c80owner = sum(p098towh,p098tobl,p098toai,p098toas,p098toot) - c80rente
• renter occupied
  c80rente = sum(p098rewh,p098rebl,p098reai,p098reas,p098reot)

tenure by units in structure (count of occupied housing units)

* These variables were obtained from the Geolytics CD due to problems with the accuracy of the data obtained from the Census Bureau. *

• In 1 Unit Structure
  c80tstr1 = sum(Occupancy Status by Units in Structure: 1 Unit Detached, 1 Unit Attached)
• In 2 Unit Structures
  c80tstr2 = Occupancy Status by Units in Structure: 2 Units
• In 3-4 Unit Structures
  c80tstr3 = Occupancy Status by Units in Structure: 3 and 4 Units
• In 5 or more Unit Structures
  c80tstr4 = Occupancy Status by Units in Structure: 5+ Units
• Mobile homes, trailers, others
  c80tstr5 = Occupancy Status by Units in Structure: Mobile Home or Trailer, Ect.

gross rent (count of renter occupied units by monthly gross rent)

• less than $ 100
  c80gren1 = sum(p124le60,p124t_79,p124t_99)
• $ 100 to $ 199
  c80gren2 = sum(p124t119,p124t149,p124t169,p124t199)
• $ 200 to $ 299
  c80gren3 = sum(p124t249,p124t299)
• $ 300 or more
  c80gren4 = sum(p124t349,p124t399,p124t499,p124g500)
• no cash rent
  c80gren5 = (p124none)

telephone available and tenure (count of occupied housing units)

• owner occupied, telephone available
  c80tele1 = (p118ttel) - (p118rtel)
• owner occupied, telephone not available
  c80tele2 = (p118tnot) - round(p118rnot)
• renter occupied, telephone available
  c80tele3 = (p118rtel)
• owner occupied, telephone not available
  c80tele4 = (p118rnot)

vehicles available (count of occupied housing units with vehicle available)

• 1 automobile
  c80auto1 = (p123veh1)
• 2 automobiles
  c80auto2 = (p123veh2)
• 3 or more automobiles
  c80auto3 = (p123veh3)

heating fuel (count of occupied housing units)

• utility gas
  c80heat1 = round(p112ugas)
• bottled, tank or LP gas
  c80heat2 = (p112bgas)
• electricity
  c80heat3 = (p112elec)
• other
  c80heat4 = sum(p112foil,p112coal,p112wood,p112othr)
• no fuel used
  c80heat5 = (p112none)

   

C) 1990 Census: Time Series Demographic Statistics

1.The Block Group Census 1990 data were exported from the Geolytics Census 1990 CD-ROM as dBase files and then imported into the Statistical Analysis System (SAS) software for further processing and analysis.

Geo-referenced population points 1990 estimates were reported by geographic county sub-divisions known as Census Block Group. Block Groups in the 1990 Census average 452 housing units,  or 1, 100 people. The two most important reasons for compiling Census Block Group data were 1) to be able to prorate certain economic variables,  by industries within the Census Block Group,  and 2) to be able to group Census Block Group centroids according to the NOAA’s Coastal Assessment Framework (CAF). The points were imported to ArcView® GIS 3.0. Estimates were assigned watershed attributes through a GIS overlay operation with NOAA’s Coastal Assessment Framework (CAF). The demographic variables data were then summarized by NOAA’s unique code,  USGS 8-digit Hydrologic Cataloging Unit (HUC) code and Watershed (EDA,  CDA,  FDA) codes. Unique in the CAF is the intersection area of an 8-digit Cataloging Unit and Estuarine areas. County level estimates were obtained by summarizing the demographic variables by the existent 5-digit FIPS code associated to each Census Block Group point data. To obtain the deliverable Census Demographic 1990 files,  299 variables were selected from the Census 1990 Block Group database. The variable IABOVEPL (income above poverty line) was computed as the sum of Census variables p1170001 to p1170012 and variable IBELOWPL (income below poverty line) as the sum of Census variables p1170013 to p1170024.

2. Quality Control: Census Block Group centroid coordinates were plotted on the CAF’s county map as a way to verify the FIPS assignment in the Census file. Points falling on water or outside the assigned county were given a buffer of 5 miles and plotted again in the county map. This resulted in having all points in the counties as reported in the file.  The Census Block 1990 population estimates file obtained from USGS and summarized by county were checked for accuracy against The Census Block Group 1990 population estimates file summarized also by county from Census CD,  Geolytics,  Inc. Results from this comparison found small differences on only few counties as shown below:

POP90 = Persons in County (Data from Census Blocks as Provided by USGS)
POP90_1 = Persons in County (Data from Census Block Groups as Provided by Geolytics,   Inc.)

FIPS Code: POP90 / POP90_1

02290: 6, 714 / 8, 478
25023: 433, 812 / 435, 276
26147: 145, 590 / 145, 607
26163: 2, 110, 972 / 2, 111, 687
48061: 260, 067 / 260, 120
48141: 587, 392 / 591, 610
48215: 382, 921 / 383, 545

3. To obtain a Time Series Population and Housing file (1970,  1980, 1990, and 2000),   the following variables that are common to the 1970, 1980, and 2000 censuses were obtained from the CENSUS90 file  (for a complete listing of all variables in the Original CENSUS 1990 click here).

urban,  nonurban and total population (count of persons)

• urban
  c90urbn = sum(p0060001,  p0060002)
• rural
  c90nurbn = sum(p0060003,  p0060004)
• rural farm
  c90rfarm = round(p0060003)
• rural non-farm
  c90rnfar = round(p0060004)
• total population
  c90popul = sum(c90urbn, c90nurbn)

race (count of persons)

• white,  black and other
  c90white = (p0080001)
  c90black = (p0080002)
  c90other = (sum(p0080003,  p0080004, p0080005))

language (count of persons 5 years and over)

• english,  spanish,  other languages
  c90engli = (sum(p0280001,p0280011,p0280021));
  c90spani =(sum(p0280002, p0280003, p0280004, p0280012, p0280013, p0280014, p0280022, p0280023, p0280024));
  c90hloth = (sum(p0280005, p0280006, p0280007, p0280008, p0280009, p0280010, p0280015, p0280016, p0280017, p0280018, p0280019, p0280020, p0280025, p0280026, p0280027, p0280028, p0280029, p0280030));

age (count of persons)

• persons under 2 years
  c90age1 = (sum(p0130001, p0130002))
• persons 3 to 4 years
  c90age2 = (p0130003)
• persons 5 years
  c90age3 = (p0130004)
• persons 6 years
  c90age4 = (p0130005)
• persons 7 to 9 years
  c90age5 = (p0130006)
• persons 10 to 13 years
  c90age6 = (sum(p0130007, p0130008))
• persons 14 years
  c90age7 = (p0130009)
• persons 15 years
  c90age8 = (p0130010)
• persons 16 years
  c90age9 = (p0130011)
• persons 17 years
  c90age10 = (p0130012)
• persons 18 years
  c90age11 = (p0130013)
• persons 19 years
  c90age12 = (p0130014)
• persons 20 years
  c90age13 = (p0130015)
• persons 21 years
  c90age14 = (p0130016)
• persons 22 to 24 years
  c90age15 = (p0130017)
• persons 25 to 34 years
  c90age16 = (sum(p0130018, p0130019))
• persons 35 to 44 years
  c90age17 = (sum(p0130020, p0130021))
• persons 45 to 54 years
  c90age18 = (sum(p0130022, p0130023))
• persons 55 to 59 years
  c90age19 = (p0130024)
• persons 60 to 61 years
  c90age20 = (p0130025)
• persons 62 to 64 years
  c90age21 = (p0130026)
• persons 65 to 74 years
  c90age22 = sum(p0130027, p0130028)
• persons 75 and over
  90age23 = sum(p0130029, p0130030, p0130031)

sex (count of persons)

c90male = (p0070001)
c90fema = (p0070002)

family income (count of families)

• family income less than $ 9, 999
  c90fi1 = sum(p1070001, p1070002)
• family income $ 10, 000 to $ 14, 999
  c90fi2 = sum(p1070003,  p1070004)
• family income $ 15, 000 to $ 24, 999
  c90fi3 = sum(p1070005,  p1070006,  p1070007,   p1070008)
• family income $ 25, 000 to $ 49, 999
  c90fi4 = sum(p1070009,  p1070010,  p1070011,   p1070012,  p1070013, p1070014,  p1070015,  p1070016,  p1070017, p1070018)
• family income $ 50, 000 and over
  c90fi5 = sum(p1070019,  p1070020,  p1070021,   p1070022,  p1070023, p1070024,  p1070025)

school enrollment (count of persons 3 yr. old and over enrolled in school)

• persons in no college (nursery,  kindergarten,   elementary and high school)
  c90ncoll = (sum(p0540001, p0540002, p0540003, p0540004))
• persons in college
  c90colle = (sum(p0540005, p0540006))

education attainment (count of persons 25 yr. old and over)

• less than 12th grade
  c90educ1 = (sum(p0570001, p0570002))
• high school graduate
  c90educ2 = (p0570003)
• college 1 to 3 years (some college,  associate degree)
  c90educ3 = (sum(p0570004, p0570005))
• college 4 years or more (bachelors or graduate degree)
  c90educ4 = (sum(p0570006, p0570007))

occupation (count of employed persons 16 yr. old and over)

• professional,  technical and kindred workers
  (professional and specialty,  technical and related support)
  c90occu1 = (sum(p0780002, p0780003))
• executive-administrative-managerial
  (farmers and farm managers,  managers,  officials & proprietors except farm)
  c90occu2 = (p0780001)
• clerical and kindred workers
  (administrative support including clerical)
  c90occu3 = (p0780005)
• sales workers
  c90occu4 = (p0780004)
• craftsmen,  foremen,  and kindred workers
  (precision production-craft-repair)
  c90occu5 = (p0780010)
• operatives and kindred workers
  (machine operators-assemblers-inspectors)
  c90occu6 = (p0780011)
• service workers including private household
  (private household service,  protective service,   other service)
  c90occu7 = (sum(p0780006, p0780007, p0780008))
• farm laborers and farm foremen
  (farming-forestry-fishing)
  c90occu8 = (p0780009)
• laborers except farm and mine
  (transportation and material moving)
  c90occu9 = (sum(p0780012, p0780013))

industry (count of employed persons 16 yr. old and over)

• construction
  c90indu1 = (p0770003)
• manufacturing of durable goods and non-durable goods
  c90indu2 = sum(p0770004, p0770005)
• transportation
  c90indu3 = (p0770006)
• communications and other public utilities
  c90indu4 = (p0770007)
• wholesale and retail trade
  c90indu5 = sum(p0770008, p0770009)
• finance,  insurance,  business,  and repair
  c90indu6 = sum(p0770010, p0770011)
• other professional and related services
  c90indu7 = sum(p0770012, p0770013, p0770014, p0770016)
• educational services
  c90indu8 = (p0770015)
• public administration
  c90indu9 = (p0770017)
• other industries
  c90ind10 = sum(p0770001, p0770002)

poverty status (count of persons for whom poverty status is determined)

c90above = (iabovepl)
c90below = (ibelowpl)

nativity (count of persons)

• natives
  c90nativ = sum(p0420001,p0420002,p0420003,
  p0420004,p0420005,p0420006,p0420007,p0420008)
• foreign
  c90forei = (p0420009)

household relationship (count of persons)

• in family household
  c90fhous = sum(p0170001,p0170002,p0170003,
  p0170004,p0170005,p0170006,p0170007,
  p0170008,p0170009,p0170010,p0170011,p0170012)
• in group quarters
  c90gquar = sum(p0170013,p0170014,p0170015)

family type (count of families)

• all families
  c90allfa = (p0040001)
• families with female head
  c90fawfh = sum(p0220005,p0220006)

population 14 years old and over by sex
(count of persons 14 years old and over)

• male
  c90m14yr = sum(p0270001,p0270002,p0270003,p0270004,
  p0270005,p0270006)
• female
  c90f14yr = sum(p0270007,p0270008,p0270009,p0270010,
  p0270011,p0270012)

population 5 years old and over by residence
(count of persons 5 years old and over)

• same house
  c90shous = (p0430001)
• different house
  c90dhous = sum(p0430002,p0430003,p0430004,
  p0430005,p0430006,p0430007)
• abroad
  c90abroa = sum(p0430008,p0430009,p0430010)

labor force by sex (count of persons 16yrs old and over)

• male in labor force (armed forces, employed, unemployed, inmate of institution)
  c90mlfor = sum(p0710001,p0710002,p0710003)
• male other not in labor force
  c90mnlfo = (p0710004)
• female in labor force (armed forces, employed, unemployed, inmate of institution)
  c90flfor = sum(p0710005,p0710006,p0710007)
• female other not in labor force
  c90fnlfo = (p0710008)

families with female head by poverty status
(count of families with female head)

• above poverty level
  c90fhabo = sum(p1230009,p1230010,p1230011,p1230012)
• below poverty level
  c90fhbel = sum(p1230021,p1230022,p1230023,p1230024)

families by poverty status (count of families)

• families above poverty level
  c90fabov = sum(p1230001,p1230002,p1230003,p1230004,
  p1230005,p1230006,p1230007,p1230008,p1230009,
  p1230010,p1230011,p1230012)
• families below poverty level
  c90fbelo = sum(p1230013,p1230014,p1230015,p1230016,
  p1230017,p1230018,p1230019,p1230020,p1230021,
  p1230022,p1230023,p1230024)

tenure (count of occupied housing units)

• owner occupied
  c90owner = (h0080001)
• renter occupied
  c90rente = (h0080002)

tenure and units in structure (count of housing units)

• In 1 Unit Structure
  c90tstr1 = sum(h0200001,h0200002)
• In 2 Unit Structures
  c90tstr2 = (h0200003)
• In 3-4 Unit Structures
  c90tstr3 = (h0200004)
• In 5 or more Unit Structures
  c90tstr4 = sum(h0200005,h0200006,h0200007,h0200008)
• Mobile homes, trailers, others
  c90tstr5 = sum(h0200009,h0200010)

gross rent
(count of renter occupied units by monthly gross rent)

• less than $ 100
  c90gren1 = (h0430001)
• $ 100 to $ 199
  c90gren2 = sum(h0430002,h0430003)
• $ 200 to $ 299
  c90gren3 = sum(h0430004,h0430005)
• $ 300 or more
  c90gren4 = sum(h0430006,h0430007,h0430008,h0430009,
  h0430010,h0430011,h0430012,h0430013,h0430014,
  h0430015,h0430016)
• no cash rent
  c90gren5 = round(h0430017)

telephone available and tenure (count of occupied housing units)

• owner occupied, telephone available
  c90tele1 = (h0350001)
• owner occupied, telephone not available
  c90tele2 = (h0350002)
• renter occupied, telephone available
  c90tele3 = (h0350003)
• owner occupied, telephone not available
  c90tele4 = (h0350004)

vehicles available (count of occupied housing units with vehicle available)

• 1 automobile
  c90auto1 = sum(h0370002,h0370008)
• 2 automobiles
  c90auto2 = sum(h0370003,h0370009)
• 3 or more automobiles
  c90auto3 = sum(h0370004,h0370005,h0370006,
  h0370010,h0370011,h0370012)

heating fuel (count of occupied housing units)

• utility gas
  c90heat1 = (h0300001)
• bottled, tank or LP gas
  c90heat2 = (h0300002)
• electricity
  c90heat3 = (h0300003)
• other
  c90heat4 = sum(h0300004,h0300005,h0300006,h0300007,h0300008)
• no fuel used
  c90heat5 = (h0300009)

D) 2000 Census: Time Series Demographic Statistics

1. The Block Group Census 2000 data were exported from the Geolytics Census 2000 CD-ROM as dBase files and then imported into the Statistical Analysis System (SAS) software for further processing and analysis.

Geo-referenced 2000 population points were reported by geographic county sub-divisions known as Census Block Group. The method for getting the coordinates for the block groups was to use the coordinates of the block with the largest population. This was done to assure that all coordinates fell on land. The points were imported to ArcView®.   Estimates were assigned watershed attributes through a GIS overlay operation with NOAA’s Coastal Assessment Framework (CAF). The demographic variables data were then summarized by NOAA’s unique code,  USGS 8-digit Hydrologic Cataloging Unit (HUC) code and Watershed (EDA,  CDA,  FDA) codes. Unique in the CAF is the intersection area of an 8-digit Cataloging Unit and Estuarine areas. County level estimates were obtained by summarizing the demographic variables by the existent 5-digit FIPS code associated to each Census Block Group point data. Flag variables were created to inform the user that a number of points fall either outside of the county the point is supposed to be or on water. A unique 16 digit record ID (cens20id) was obtained by concatenating the following variables: state,  county,  place,   tractbna,  and bg. 

2. Quality Control on lat/lon data
As with the the other census files,  the 2000 Census file was quality control on lat/lon data using same methodology.

The CENSUS file was plotted in NOAA’s 1990 county file. An assessment variable called "LL_FLAG" was created for assessing lat/lon data. The codes in the LL_FLAG are:

L   = Correct FIPS,  plots on land (205,452 records)

W = Correct FIPS,  plots on water (229 records)

5   = Incorrect FIPS,  but within 5 miles of correct FIPS (considered a good coordinate for purpose of assigning NOAA watershed codes) (67 records)

O  = Alaska and Hawaii points,  outside of CAF (1,165 records)

N = New county in 2000 (Dade County, FL) that does not exist in 1990 county map file (1,211 records)

3. To obtain a Time Series Population and Housing file (1970, 1980, 1990 and 2000), the following variables that are common to the 1970, 1980, 1990, and 2000 censuses were obtained from the CENSUS2000file.

urban, nonurban and total population (count of persons)

• urban
  c00urbn = (P005002)
• rural
  c00nurbn = (P005005)
• rural farm
  c00rfarm = (P005006)
• rural non-farm
  c00rnfar = (P005007)
• total population
  c00popul = (P005001)

race (count of persons)

• white, black, and other
  c00white = (P006002)
  c00black = (P006003)
  c00other = (sum(P006004, P006005, P006006, P006007, P006008))

language (count of persons 5 years and over)

• english, spanish, other languages
  c00engli = (sum(P019003, P019025, P019047))
  c00spani = (sum(P019004, P019026, P019048))
  c00hloth = (sum(P019009, P019014, P019019, P019031, P019036, P019041, P019053, P019058, P019063))

age (count of persons)

• persons under 2 years
  c00age1 = (sum(P008003, P008004, P008005, P008042, P008043, P008044))
• persons 3 to 4 years
  c00age2 = (sum(P008006, P008007, P008045, P008046))
• persons 5 years
  c00age3 = (sum(P008008, P008047))
• persons 6 years
  c00age4 = (sum(P008009, P008048))
• persons 7 to 9 years
  c00age5 = (sum(P008010, P008011, P008012, P008049, P008050, P008051))
• persons 10 to 13 years
  c00age6 = (sum(P008013, P008014, P008015, P008016, P008052, P008053, P008054, P008055))
• persons 14 years
  c00age7 = (sum(P008017, P008056))
• persons 15 years
  c00age8 = (sum(P008018, P008057))
• persons 16 years
  c00age9 = (sum(P008019, P008058))
• persons 17 years
  c00age10 = (sum(P008020, P008059))
• persons 18 years
  c00age11 = (sum(P008021, P008060))
• persons 19 years
  c00age12 = (sum(P008022, P008061))
• persons 20 years
  c00age13 = (sum(P008023, P008062))
• persons 21 years
  c00age14 = (sum(P008024, P008063))
• persons 22 to 24 years
  c00age15 = (sum(P008025, P008064))
• persons 25 to 34 years
  c00age16 = (sum(P008026, P008027, P008065, P008066))
• persons 35 to 44 years
  c00age17 = (sum(P008028, P008029, P008067, P008068))
• persons 45 to 54 years
  c00age18 = (sum(P008030, P008031, P008069, P008070))
• persons 55 to 59 years
  c00age19 = (sum(P008032, P008071))
• persons 60 to 61 years
  c00age20 = (sum(P008033, P008072))
• persons 62 to 64 years
  c00age21 = (sum(P008034, P008073))
• persons 65 to 74 years
  c00age22 = (sum(P008035, P008036, P008037, P008074, P008075, P008076))
• persons 75 and over
  c00age23 = (sum(P008038, P008039, P008040, P008077, P008078, P008079))

sex (count of persons)

c00male = (P008002)
c00fema = (P008041)

family income (count of families)

• family income less than $9,999
  c00fi1 = (P076002)
• family income $10,000 to $14,999
  c00fi2 = (P076003)
• family income $15,000 to $24,999
  c00fi3 = (sum(P076004, P076005))
• family income $25,000 to $49,999
  c00fi4 = (sum(P076006, P076007, P076008, P076009, P076010))
• family income $50,000 and over
  c00fi5 = (sum(P076011, P076012, P076013, P076014, P076015, P076016, P076017))

school enrollment (count of persons 3 yr. old and over enrolled in school)

• persons not in college (enrolled in nursery, kindergarten, elementary, and high school)
  c00ncoll = (sum(P036003, P036006, P036009, P036012, P036015, P036026, P036029, P036032, P036035, P036038))
• persons in college
  c00colle = (sum(P036018, P036021, P036041, P036044))

education attainment (count of persons 25 yr. old and over)

• less than 12th grade
  c00educ1 = (sum(P037004, P037005, P037006, P037007, P037008, P037009, P037010, P037021, P037022, P037023, P037024, P037025, P037026, P037027))
• high school graduate
  c00educ2 = (sum(P037011, P037028))
• college 1 to 3 years (some college, associate degree)
  c00educ3 = (sum(P037012, P037013, P037014, P037029, P037030, P037031))
• college 4 years or more (bachelors or graduate degree)
  c00educ4 = (sum(P037015, P037016, P037017, P037018, P037032, P037033, P037034, P037035))

occupation (count of employed persons 16 yr. old and over)

• professional, technical and kindred workers
  (professional and specialty, technical and related support)
  c00occu1 = (sum(P050010, P050057))
• executive-administrative-managerial
  (farmers and farm managers, managers, officials & proprietors except farm)
  c00occu2 = (sum(P050004, P050051))
• clerical and kindred workers
  (administrative support including clerical)
  c00occu3 = (sum(P050033, P050080))
• sales workers
  c00occu4 = (sum(P050032, P050079))
• craftsmen, foremen, and kindred workers
  (precision production-craft -repair)
  c00occu5 = (sum(P050040, P050042, P050087, P050089))
• operatives and kindred workers
  (machine operators-assemblers-inspectors)
  c00occu6 = (sum(P050036, P050083))
• service workers including private household
  (private household service, protective service, other service)
  c00occu7 = (sum(P050023, P050070))
• farm laborers and farm foremen
  (farming-forestry-fishing)
  c00occu8 = (sum(P050034, P050081))
• laborers except farm and mine
  (transportation and material moving)
  c00occu9 = (sum(P050043, P050090))

industry (count of employed persons 16 yr. old and over)

• construction
  c00indu1 = (sum(P049006, P049033))
• manufacturing of durable goods and non-durable goods
  c00indu2 = (sum(P049007, P049034))
• transportation
  c00indu3 = (sum(P049011, P049038))
• communications and other public utilities
  c00indu4 = (sum(P049012, P049013, P049039, P049040))
• whole sale and retail trade
  c00indu5 = (sum(P049008, P049009, P049035, P049036))
• finance, insurance, business, and repair
  c00indu6 = (sum(P049014, P049041))
• other profession and related services
  c00indu7 = (sum(P049017, P049044))
• educational services
  c00indu8 = (sum(P049022, P049049))
• public administration
  c00indu9 = (sum(P049028, P049055))
• other industries
  c00indu10 = (sum(P049003, P049023, P049024, P049027, P049030, P049050, P049051, P049054))

poverty status (count of persons for whom poverty status is determined)

c00above = (P089021)
c00below = (P089002)

nativity (count of persons in family households)

• natives
  c00nativ = (P021002)
• foreign
  c00forei = (P021013)

household relationship (count of persons in family households)

• in family households
  c00fhous = (P009002)
• in group quarters
  c00gquar = (P009025)

family type (count of families)

• all families
  c00allfa = (P015001)
• families with female head
  c00fawfh = (P015015)

population 14 years old and over by sex (count of persons 14 yrs. old and over)

• male
  c00m14yr = (P008002 - sum(P008003, P008004, P008005, P008006, P008007, P008008, P008009, P008010, P008011, P008012, P008013, P008014, P008015, P008016))
• female
  c00f14yr = (P008041 - sum(P008042, P008043, P008044, P008045, P008046, P008047, P008048, P008049, P008050, P008051, P008052, P008053, P008054, P008055))

population 5 years old and over by residence
(count of persons 5 yrs. old and over)

• same house
  c00shous = (P024002)
• different house
  c00dhous = (P024003)
• abroad
  c00abroa = (P024018)

labor force by sex (count of persons 16yrs old and over)

• male in labor force (armed forces, employed, unemployed)
  c00mlfor = (P043003)
• male other not in labor force
  c00mnlfo = (P043008)
• females in labor force (armed forces, employed, unemployed)
  c00flfor = (P043010)
• females other not in labor force
  c00fnlfo = (P043015)

families with female head by poverty status
(count of families with female head)

• above poverty level
  c00fhabo = (P090037)
• below poverty level
  c00fhbel = (P090017)

families by poverty status (count of families)

• families above poverty level
  c00fabov = (sum(P090023, P090030, P090036))
• families below poverty level
  c00fbelo = (sum(P090003, P090010, P090016))

tenure (count of occupied housing units)

• owner occupied
  c00owner = (H007002)
• renter occupied
  c00rente = (H007003)

tenure and units in structure (count of housing units)

• In 1 Unit Structure
  c00tstr1 = (sum(H030002, H030003))
• In 2 Unit Structure
  c00tstr2 = (H030004)
• In 3-4 Unit Structure
  c00tstr3 = (H030005)
• In 5 or more Unit Structure
  c00tstr4 = (sum(H030006, H030007, H030008, H030009))
• Mobile homes, trailers, others
  c00tstr5 = (sum(H030010, H030011))

gross rent (count of renter occupied units by monthly gross rent)

• less than $100
  c00gren1 = (H062003)
• $100 to $199
  c00gren2 = (sum(H062004, H062005))
• $200 to $299
  c00gren3 = (sum(H062006, H062007))
• $300 or more
  c00gren4 = (sum(H062008, H062009, H062010, H062011, H062012, H062013, H062014, H062015, H062016, H062017, H062018, H062019, H062019, H062020, H062021, H062022, H062023)
• no cash rent
  c00gren5 = (H062024)

telephone available and tenure (count of occupied housing units)

• owner occupied, telephone available
  c00tele1 = (H043003)
• owner occupied, telephone not available
  c00tele2 = (H043011)
• renter occupied, telephone available
  c00tele3 = (H043020)
• renter occupied, telephone not available
  c00tele4 = (H043028)

vehicle available (count of occupied housing units with vehicle available)

• 1 automobile
  c00auto1 = (sum(H044004, H044011))
• 2 automobiles
  c00auto2 = (sum(H044005, H044012))
• 3 or more automobiles
  c00auto3 = (sum(H044006, H044007, H044008, H044013, H044014, H044015))

heating fuel (count of occupied housing units)

• utility gas
  c00heat1 = (H040002)
• bottled, tank or LP gas
  c00heat2 = (H040003)
• electricity
  c00heat3 = (H040004)
• other
  c00heat4 = (H040005, H040006, H040007, H040008, H040009)
• no fuel used
  c00heat5 = (H040010)

year structure built (count of housing units)

h0340002
h0340003
h0340004
h0340005
h0340006
h0340007
h0340008
h0340009
h0340010

 

E) 2000 Census Extended variables:

This digram shows the many geographic types for which Census data are available and the heirarchical relationships between geographic types.

An extended list of variables is available for the 2000 Census Data. The data are available for nine distinct spatial aggregations: Block Group, Blocks within Coastal Zone, County, State, Zip Code, Place, NOAA's Coastal Watershed, USGS Hydrologic Cataloging Units, and Voting Districts.

The U.S. Census Bureau provides data for a range of geographic types from the United States down to a Census Block. A detailed description of Census geography terminology can be obtained from the U.S. Census Bureau web site (American Factfinder - http://factfinder.census.gov/home/en/epss/glossary_a.html).

2000 Census data aggregated by Block Group, County, State, NOAA's Coastal Watershed, and USGS Hydrologic Cataloging Units were obtained from Block Group Census 2000 level data (Geolytics - CensusCD 2000 - Long Form SF3, Release 2.1). While 2000 Census data aggregated by Zip Code, Place, Blocks within the Coastal Zone, and Voting districts were obtained from Block Level Census 2000 data (Geolytics - CensusCD 2000 - Short Form Blocks, Release 1.1).

total population (count of persons)

Block Level Data

P001001

race (count of persons)

Block Group Level Data

P006001
P006002
P006003
P006004
P006005
P006006
P006007
P006008

Block Level Data

P007001
P007002
P007003
P007004
P007005
P007006
P007007
P007008

hispanic population by race (count of persons)

Block Group Level Data

P007001
P007002
P007003
P007004
P007005
P007006
P007007
P007008
P007009
P007010
P007011
P007012
P007013
P007014
P007015
P007016
P007017

Block Level Data

P008001
P008002
P008003
P008004
P008005
P008006
P008007
P008008
P008009
P008010
P008011
P008012
P008013
P008014
P008015
P008016
P008017

age of population by sex (count of persons)

Block Level Data

P012001
P012002
P012003
P012004
P012005
P012006
P012007
P012008
P012009
P012010
P012011
P012012
P012013
P012014
P012015
P012016
P012017
P012018
P012019
P012020
P012021
P012022
P012023
P012024
P012025
P012026
P012027
P012028
P012029
P012029
P012030
P012031
P012032
P012033
P012034
P012035
P012036
P012037
P012038
P012039
P012040
P012041
P012042
P012043
P012044
P012045
P012046
P012047
P012048
P012049

total number of households (count of households)

Block Level Data

P015001

population in households (count of persons in households)

Block Level Data

P016001

average household size (count of persons/household)

Block Level Data

P017001

total number of families (count of families)

Block Level Data

P031001

persons 5 years and over by residence (count of persons 5 years old and over)

Block Group Level Data

P024001
P024002
P024003

place of work (count of employed persons 16 years old and over)

Block Group Level Data

P026001
P026002
P026003
P026004
P026005

means of transportation to work (count of employed persons 16 years old and over)

Block Group Level Data

P030001
P030002
P030003
P030004
P030005
P030006
P030007
P030008
P030009
P030010
P030011
P030012
P030013
P030014
P030015
P030016

household income (count of households)

Block Group Level Data

P052001
P052002
P052003
P052004
P052005
P052006
P052007
P052008
P052009
P052010
P052011
P052012
P052013
P052014
P052015
P052016
P052017

median household income (dollars/household)

Block Group Level Data

P053001

family income (count of families)

Block Group Level Data

P076001
P076002
P076003
P076004
P076005
P076006
P076007
P076008
P076009
P076010
P076011
P076012
P076013
P076014
P076015
P076016
P076017

per capita income (dollars/person)

Block Group Level Data

P082001

total housing units (count of housing units)

Block Group Level Data

H001001

Block Level Data

H001001

occupancy status (count of housing units)

Block Group Level Data

H006001
H006002
H006003

Block Level Data

H003001
H003002
H003003

tenure (count of occupied housing units)

Block Level Data

H004001
H004002
H004003

vacancy status (count of vacant housing units)

Block Group Level Data

H008001
H008002
H008003
H008004
H008005
H008006
H008007

Block Level Data

H005001
H005002
H005003
H005004
H005005
H005006
H005007

plumbing facilities (count of housing units)

Block Group Level Data

H047001
H047002
H047003

value owner occupied housing units (count of owner occupied housing units)

Block Group Level Data

H084001
H084002
H084003
H084004
H084005
H084006
H084007
H084008
H084009
H084010
H084011
H084012
H084013
H084014
H084015
H084016
H084017
H084018
H084019
H084020
H084021
H084022
H084023
H084024
H084025

The universe (unit) of variables for characteristics in the Time Series Demographic Statistics 1970, 1980, 1990 and 2000 censuses is given below:

Contact for Data Processing:

Percy A. Pacheco
NOS - Special Projects Office (SP)
Coastal Resources Assessment Branch
1305 East West Highway,  SSMC4,  9^th Floor
Silver Spring,  Maryland 20910
Tel: 301-713-3000
Fax:301-713-4384
Email:percy.pacheco@noaa.gov

Citation:

National Coastal Assessments (NCA) Branch,  Special Projects Office (SP),  Management and Budget Office, National Ocean Service (NOS),  National Oceanic and Atmospheric Administration (NOAA). Silver Spring,  Maryland.

For Additional Information:

Special Projects Office (SPO),  NOS/NOAA
Coastal Resources Assessment Branch
1305 East West Highway,  SSMC4,  9^th Floor
Silver Spring,  Maryland 20910
Tel: 301-713-3000
Fax: 301-713-4384

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