The S&O 2060 Outlook is comprised of annual demographic estimates and projections for the period 2010 to 2060.

 

The S&O 2060 Outlook database includes single year of data iterated by gender and race/origin.  These data include components of change (births, deaths, migration) data and single year of age data for ages under 1 year, 1 year, ... 84 years and 85 years and over.

 

Estimates and Projections by ProximityOne.

 

Geography available: county up

 

See release schedule.

 

Sample Data

Sample dataset for Sedgwick County (Wichita), Kansas (XLS): http://proximityone.com/outlook/de120173.xls

Standard DE-1 County Outlook Estimates and Projections Dataset

These data and organization of the dataset are proprietary to ProximityOne.

 

Sedgwick County Demographic Profile (above dataset processed using CV XE tools)

Example using White alone population only, aggregating gender detail, annual projection period to 2020

... first 10 years of total 50 year projection period

... scroll vertically across ages; scroll horizontally across years.

Population 2010-20: m010
Sedgwick County KS (20173)
White alone (002)20102011201220132014201520162017201820192020
Total 380,482 382,764 385,731 388,642 391,475 394,232 396,926 399,555 402,109 404,618 407,069
Age 0-4 25,833 25,811 25,664 25,622 25,535 25,630 25,724 25,823 25,919 26,026 26,139
Age 5-9 25,567 25,430 25,749 25,849 25,987 25,899 25,932 25,785 25,743 25,655 25,750
Age 10-14 25,427 25,554 25,594 25,651 25,738 25,673 25,591 25,909 26,009 26,148 26,060
Age 15-19 25,006 25,513 25,389 25,297 25,283 25,500 25,681 25,720 25,777 25,864 25,800
Age 20-24 25,152 24,193 24,016 24,277 24,592 25,018 25,576 25,452 25,362 25,348 25,563
Age 25-29 27,894 27,890 27,644 26,900 26,174 25,153 24,253 24,076 24,335 24,649 25,073
Age 30-34 24,716 25,368 26,210 27,019 27,640 27,891 27,941 27,696 26,956 26,233 25,216
Age 35-39 23,347 23,068 23,119 23,454 23,901 24,699 25,401 26,238 27,043 27,661 27,910
Age 40-44 23,428 23,581 23,610 23,633 23,535 23,281 23,058 23,110 23,442 23,886 24,677
Age 45-49 27,591 26,344 25,355 24,347 23,503 23,286 23,492 23,520 23,542 23,445 23,194
Age 50-54 29,233 29,259 28,989 28,659 28,216 27,311 26,136 25,161 24,167 23,337 23,124
Age 55-59 26,034 26,964 27,703 28,122 28,479 28,782 28,861 28,595 28,271 27,835 26,948
Age 60-64 21,041 22,370 22,824 23,524 24,357 25,393 26,347 27,063 27,469 27,814 28,109
Age 65-69 14,414 14,966 16,668 18,061 19,119 20,178 21,485 21,921 22,593 23,388 24,375
Age 70-74 10,779 11,022 11,237 11,780 12,621 13,400 13,956 15,539 16,834 17,813 18,787
Age 75-79 9,734 9,581 9,616 9,582 9,624 9,588 9,802 9,997 10,488 11,241 11,933
Age 80-84 7,595 7,685 7,861 8,061 8,134 8,130 7,998 8,028 8,005 8,038 8,012
Age 85-89 5,150 5,320 5,352 5,426 5,401 5,531 5,604 5,727 5,872 5,907 5,912
Age 90-94 2,031 2,272 2,504 2,636 2,796 2,957 3,052 3,061 3,097 3,080 3,168
Age 95-99 458 520 571 681 771 862 962 1,055 1,108 1,174 1,241
Age 100+ 52 53 57 62 66 71 75 77 78 78 78
Age 5-17 66,396 66,205 66,429 66,594 66,872 67,052 67,127 67,218 67,124 67,134 67,369
Age 18-34 87,366 87,743 88,171 88,399 88,543 88,081 87,847 87,421 87,058 86,763 86,093
Age 15-44 149,543 149,613 149,986 150,579 151,126 151,541 151,911 152,293 152,915 153,640 154,239
Age 16 & over 298,564 300,939 303,761 306,433 309,132 311,734 314,468 317,035 319,293 321,619 323,889
Age 18 & over 288,253 290,748 293,638 296,426 299,068 301,550 304,075 306,514 309,066 311,458 313,561
Age 65 & over 50,213 51,418 53,867 56,289 58,534 60,717 62,932 65,406 68,074 70,718 73,506
Age 85 & over 7,691 8,165 8,484 8,804 9,035 9,420 9,692 9,920 10,154 10,239 10,399
Single Year of Age:20102011201220132014201520162017201820192020
Age 0 5,092 5,100 5,113 5,141 5,160 5,177 5,195 5,213 5,237 5,268 5,290
Age 1 5,235 5,058 5,077 5,090 5,118 5,136 5,153 5,171 5,189 5,213 5,244
Age 2 5,176 5,229 5,063 5,082 5,095 5,123 5,141 5,158 5,176 5,194 5,218
Age 3 5,258 5,171 5,235 5,069 5,088 5,100 5,128 5,147 5,164 5,182 5,200
Age 4 5,072 5,253 5,177 5,240 5,075 5,094 5,106 5,134 5,153 5,170 5,187
Age 5 5,180 5,067 5,259 5,183 5,246 5,081 5,100 5,112 5,140 5,159 5,176
Age 6 5,125 5,175 5,073 5,265 5,189 5,253 5,087 5,106 5,119 5,146 5,165
Age 7 5,106 5,120 5,182 5,080 5,272 5,195 5,259 5,093 5,112 5,125 5,153
Age 8 4,970 5,101 5,127 5,188 5,086 5,278 5,202 5,265 5,100 5,119 5,131
Age 9 5,186 4,966 5,108 5,133 5,194 5,093 5,284 5,208 5,272 5,106 5,125
Age 10 5,277 5,182 4,972 5,114 5,140 5,201 5,099 5,291 5,214 5,278 5,113
Age 11 5,070 5,273 5,188 4,979 5,121 5,146 5,207 5,106 5,297 5,221 5,285
Age 12 5,081 5,066 5,279 5,195 4,985 5,128 5,153 5,214 5,112 5,304 5,228
Age 13 4,963 5,076 5,072 5,286 5,201 4,992 5,134 5,159 5,220 5,119 5,310
Age 14 5,036 4,958 5,082 5,078 5,291 5,207 4,997 5,140 5,165 5,226 5,124
Age 15 5,091 5,030 4,963 5,087 5,083 5,297 5,212 5,003 5,145 5,170 5,231
Age 16 5,113 5,085 5,035 4,968 5,092 5,088 5,301 5,216 5,007 5,149 5,175
Age 17 5,198 5,106 5,088 5,039 4,972 5,096 5,091 5,305 5,220 5,011 5,153
Age 18 5,110 5,190 5,109 5,092 5,042 4,975 5,099 5,095 5,308 5,223 5,014
Age 19 4,494 5,102 5,193 5,112 5,094 5,045 4,978 5,102 5,097 5,310 5,226
Age 20 4,681 4,486 5,104 5,195 5,114 5,097 5,047 4,980 5,104 5,100 5,313
Age 21 4,812 4,673 4,489 5,106 5,197 5,116 5,099 5,049 4,983 5,106 5,102
Age 22 4,950 4,803 4,675 4,491 5,108 5,199 5,118 5,101 5,051 4,984 5,108
Age 23 5,300 4,941 4,805 4,677 4,493 5,110 5,201 5,120 5,102 5,053 4,986
Age 24 5,409 5,291 4,943 4,807 4,679 4,496 5,112 5,202 5,122 5,104 5,055
Age 25 5,716 5,400 5,292 4,945 4,810 4,682 4,498 5,114 5,204 5,124 5,106
Age 26 5,549 5,707 5,402 5,295 4,947 4,812 4,684 4,501 5,116 5,206 5,126
Age 27 5,704 5,540 5,709 5,404 5,297 4,950 4,815 4,687 4,504 5,118 5,209
Age 28 5,556 5,695 5,543 5,711 5,407 5,300 4,953 4,818 4,690 4,508 5,121
Age 29 5,369 5,547 5,698 5,545 5,713 5,409 5,302 4,956 4,821 4,693 4,511
Age 30 5,475 5,360 5,550 5,700 5,547 5,715 5,411 5,305 4,959 4,824 4,696
Age 31 4,937 5,466 5,363 5,552 5,702 5,549 5,717 5,414 5,307 4,961 4,826
Age 32 4,905 4,929 5,468 5,365 5,554 5,703 5,551 5,719 5,416 5,309 4,964
Age 33 4,725 4,896 4,931 5,470 5,366 5,555 5,705 5,553 5,721 5,417 5,311
Age 34 4,674 4,716 4,898 4,933 5,471 5,368 5,556 5,706 5,554 5,722 5,419
Age 35 4,685 4,665 4,718 4,900 4,934 5,472 5,369 5,557 5,707 5,555 5,722
Age 36 4,498 4,676 4,666 4,719 4,901 4,935 5,473 5,370 5,558 5,707 5,555
Age 37 4,579 4,488 4,677 4,668 4,720 4,902 4,936 5,473 5,370 5,558 5,707
Age 38 4,681 4,569 4,489 4,677 4,668 4,721 4,902 4,936 5,472 5,370 5,557
Age 39 4,904 4,670 4,569 4,490 4,677 4,668 4,721 4,902 4,936 5,471 5,369
Age 40 4,944 4,892 4,670 4,569 4,490 4,677 4,668 4,721 4,901 4,935 5,470
Age 41 4,596 4,932 4,891 4,669 4,568 4,489 4,676 4,667 4,720 4,900 4,934
Age 42 4,553 4,584 4,930 4,889 4,667 4,567 4,488 4,674 4,665 4,718 4,898
Age 43 4,647 4,540 4,582 4,927 4,886 4,665 4,565 4,486 4,672 4,663 4,716
Age 44 4,688 4,633 4,538 4,579 4,924 4,883 4,662 4,562 4,483 4,669 4,660
Age 45 5,153 4,674 4,630 4,534 4,576 4,920 4,879 4,659 4,559 4,480 4,666
Age 46 5,431 5,137 4,669 4,626 4,531 4,572 4,915 4,875 4,655 4,555 4,477
Age 47 5,546 5,413 5,131 4,665 4,621 4,526 4,567 4,909 4,869 4,650 4,550
Age 48 5,613 5,527 5,406 5,124 4,659 4,616 4,521 4,562 4,903 4,863 4,644
Age 49 5,848 5,593 5,519 5,398 5,117 4,653 4,610 4,515 4,556 4,896 4,857
Age 50 6,030 5,827 5,584 5,510 5,389 5,109 4,647 4,604 4,509 4,550 4,889
Age 51 5,834 6,008 5,817 5,575 5,500 5,380 5,101 4,640 4,597 4,503 4,543
Age 52 5,829 5,812 5,996 5,806 5,564 5,490 5,370 5,092 4,632 4,589 4,496
Age 53 5,831 5,806 5,800 5,983 5,793 5,553 5,479 5,359 5,082 4,624 4,581
Age 54 5,709 5,806 5,792 5,786 5,969 5,780 5,540 5,466 5,347 5,071 4,614
Age 55 5,659 5,683 5,791 5,777 5,771 5,953 5,764 5,526 5,452 5,334 5,058
Age 56 5,403 5,631 5,666 5,774 5,760 5,753 5,935 5,747 5,509 5,436 5,318
Age 57 5,331 5,374 5,613 5,647 5,754 5,740 5,734 5,915 5,728 5,491 5,419
Age 58 5,006 5,301 5,355 5,592 5,626 5,733 5,719 5,713 5,892 5,706 5,471
Age 59 4,635 4,975 5,279 5,333 5,568 5,603 5,709 5,695 5,689 5,868 5,683
Age 60 4,503 4,604 4,953 5,255 5,309 5,543 5,577 5,682 5,668 5,662 5,840
Age 61 4,456 4,470 4,582 4,928 5,229 5,282 5,515 5,549 5,653 5,639 5,633
Age 62 4,518 4,421 4,446 4,557 4,901 5,199 5,252 5,483 5,517 5,621 5,607
Age 63 4,436 4,480 4,394 4,420 4,529 4,871 5,167 5,219 5,449 5,482 5,585
Age 64 3,128 4,394 4,449 4,364 4,389 4,498 4,837 5,130 5,182 5,409 5,443
Age 65 3,270 3,095 4,360 4,414 4,330 4,355 4,462 4,798 5,088 5,140 5,365
Age 66 3,233 3,232 3,069 4,321 4,374 4,291 4,316 4,422 4,754 5,042 5,093
Age 67 2,957 3,191 3,201 3,040 4,278 4,330 4,248 4,272 4,378 4,706 4,990
Age 68 2,573 2,915 3,157 3,167 3,008 4,230 4,281 4,201 4,224 4,328 4,652
Age 69 2,381 2,533 2,881 3,120 3,129 2,973 4,177 4,228 4,149 4,172 4,275
Age 70 2,281 2,341 2,501 2,844 3,079 3,089 2,934 4,121 4,171 4,092 4,116
Age 71 2,183 2,243 2,302 2,460 2,797 3,028 3,037 2,886 4,052 4,102 4,025
Age 72 2,220 2,143 2,203 2,260 2,415 2,746 2,974 2,982 2,834 3,979 4,027
Age 73 2,164 2,176 2,101 2,159 2,216 2,368 2,692 2,915 2,924 2,778 3,901
Age 74 1,931 2,118 2,130 2,057 2,113 2,169 2,318 2,635 2,853 2,862 2,719
Age 75 2,113 1,887 2,070 2,082 2,010 2,065 2,119 2,265 2,575 2,788 2,797
Age 76 1,910 2,061 1,840 2,019 2,030 1,960 2,014 2,067 2,209 2,511 2,719
Age 77 2,020 1,858 2,005 1,790 1,964 1,975 1,907 1,959 2,011 2,149 2,443
Age 78 1,875 1,960 1,803 1,945 1,737 1,906 1,917 1,851 1,902 1,951 2,085
Age 79 1,816 1,815 1,898 1,746 1,883 1,682 1,845 1,855 1,791 1,841 1,889
Age 80 1,835 1,753 1,752 1,832 1,685 1,818 1,623 1,781 1,791 1,729 1,777
Age 81 1,516 1,766 1,687 1,686 1,763 1,622 1,749 1,562 1,714 1,723 1,664
Age 82 1,488 1,453 1,693 1,617 1,616 1,690 1,554 1,677 1,498 1,643 1,652
Age 83 1,367 1,419 1,386 1,614 1,542 1,541 1,611 1,482 1,599 1,428 1,566
Age 84 1,389 1,294 1,344 1,312 1,528 1,460 1,459 1,526 1,403 1,514 1,352
Age 85 1,327 1,304 1,215 1,262 1,232 1,435 1,371 1,370 1,433 1,318 1,422
Age 86 1,160 1,234 1,213 1,131 1,174 1,146 1,335 1,275 1,275 1,333 1,226
Age 87 987 1,068 1,137 1,118 1,041 1,081 1,056 1,230 1,175 1,174 1,227
Age 88 901 900 974 1,037 1,019 950 986 963 1,121 1,071 1,070
Age 89 775 813 812 879 936 919 857 889 869 1,012 967
Age 90 629 692 726 725 785 835 821 765 794 775 903
Age 91 502 555 611 641 640 693 737 725 675 701 685
Age 92 419 438 484 533 559 558 604 643 632 589 611
Age 93 266 361 377 417 459 481 481 520 554 544 507
Age 94 215 226 306 320 354 389 408 408 442 470 462
Age 95 172 180 189 256 267 296 325 341 341 369 393
Age 96 115 141 148 155 210 220 243 268 281 280 304
Age 97 72 93 115 120 126 170 178 197 217 227 227
Age 98 61 57 74 91 96 100 136 142 157 173 182
Age 99 38 48 45 59 72 75 79 107 112 124 136
Age 100-104 50 51 55 60 64 68 72 74 75 75 75
Age 105-109 1 1 1 1 1 1 1 1 1 2 1
Age 110+ 1 1 1 1 1 1 1 1 1 2 1

Notes
  developed using ProximityOne Modeler

 

Additional examples

•Broward County Florida -- http://proximityone.com/outlook_de1_2020_12011.htm

     total population and Hispanic population projections to 2020 by single year of age

 

Using the DE1 XLS file ...

•Navigate to row 28 column AC.  This cell shows the 2030 projected White alone male population age 26 in Sedgwick County.
•The time series data for this item is arranged across the columns (2010 annually through 2060).
•The item descriptor/variable name is shown in cell 28E -- P026MW -- see details in record content structure below.
•All projected values are based on a model and historical data and trends/relationships.  The models reflect assumptions.
•We use county specific models; projections are not controlled to state or higher level geography.
•Projections reflect a "mid-series" or most likely scenario.  Alternative projections can be developed using the Modeler software.
•Projections are unrelated to any other (non ProximityOne; e.g. Census Bureau) projections.
•Updated projected values will reflect a new/different set of historical data and possibly revised assumptions.

 

General Structural Notes

•Data in the sample file may differ from most recent vintage projections.
•Data in the sample file are not intended for any actual use and provided for illustrative purposes only.
•Data are organized with columns/fields as described in the record content description below.
•The record structure is designed to be consistent/the same/ across all Outlook datasets.
•This dataset is referred to as the standard DE-1 county Outlook estimates and projections.
•There are no summary/aggregate data for population groups, gender, or age in the dataset.
•Variations on this dataset exist for Outlook 5 year, Outlook 2030 and Outlook 2060 (shown in example).
•Each record contains codes and time-series data as described in the record content section below.
•The record/file structure are designed for analysis or further processing.  In general, the file it is not organized for direct consumption.
•The data may be aggregated, analyzed and displayed using CV XE software tools.

 

•The sample dataset is shows an example of a full set of detailed age-race/origin-gender for a typical county.
•The dataset contains a header record followed by 1,648 data records -- for this county.
•The composite all U.S. county data exceed 5 million records.

 

Population Groups

Sets of rows are provided for these race/origin groups (the sum of groups 001 through 070 is total population).

Not all counties contain data records for all population groups (only where population exist for that group).

Each population group is comprised of 206 age/gender records (there are always 206 records even if zero population).

•001 -- White Alone
•002 -- Black alone
•004 -- American Indian/Alaskan Native alone
•006 -- Native Hawaiian/Other Pacific Islander alone
•012 -- Some other race alone
•070 -- Two or more races
•400 -- Hispanic

 

Age/Gender Groups

Within each population group there are a set of population by age by gender records.

The 206 age/gender records are organized as follows:

•103 records -- male population of this population group by single year of age
•103 records -- female population of this population group by single year of age

 

Each of the 103 gender age groups shows data by age:

•ages 0 - 99 (each a separate record)
•100 -- a record for the age group 100 - 104
•102 -- a record for the age group 105 - 109
•103 -- a record for ages 110 and above

 

Data Record Content -- scroll section
Field Item DescriptionItemNameNotes/ValuesFormat
1Dataset IDDATASET  C,10
2Geographic Summary LevelSUMLEVC,3
3Geographic Identifier (SSCCCTTTTTBBBB)GEOID  C,15
4ReservedRES1  C,4
5ITEMITEM  C,10
6FORMATFORMAT  C,15
9D2010D2010  N,9,0
10D2011D2011  N,9,0
11D2012D2012  N,9,0
.........  fmt
57D2059D2059  fmt
58D2060D2060  fmt


ITEM Codes and Descriptions
Item DescriptionItem CodeNotes  
Total PopulationTOTPOP   
Population Age 0P000GRAMD    
Population Age 1P001GRAMD    
  ... continues by age ......    
Population Age 84P084GRAMD    
Population Age 85upP085GRAMD    

Item code is 9 characters; zero is required for total or where category not applicable.
sample codes:
P015MHC00 -- Population age 15, male, Hawaiian, in combination
P01500000 -- Population age 15, total
P0150000D -- Deaths, total population, age 15
P015M00I0 -- International migration, total male population, age 15

where GRAMD (see in item code field in above table):
CodeValueDescription
G: GenderMMale
  FFemale
R: Race WWhite alone
  BBlack alone
  IAmerican Indian/Native Alaskan alone -- AIAN
  AAsian alone
  NNative Hawaiian/Other Pacific Islander alone -- NHPI
  H  Native Hawaiian alone
  SSome Other Race alone
  2Two or More Races
A: Attribute HHispanic
  Cin Combination
  DDaytime
M: Migration HDomestic
  CInternational
D: Deaths DDeaths

 

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