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ZIP Code Area 89104 Detailed Age-Race/Origin Profile

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What are the population patterns by age/age group in census tract(s) or ZIP code area(s) of interest? How do these patterns vary by race/origin? What can these data tell you about variation/potential in business opportunities? What tracts or ZIP code areas might have underserved populations relative to your programs/goals? These types of questions can be answered by the types of data/data organization reviewed here.

Detailed age-race/origin demographics for ZIP Code area 89104 are provided in this section.
  • Table 1 -- single year of age (SYOA) by race/origin
  • Table 2 -- selected age cohorts by race/origin
Similarly structured profiles are also available for census tracts, counties and other geography. View profiles for other ZIP Code areas.

Tables shown below can be used to view the size of a specific age or age-group relative to the total population. There are a myriad of more focused applications such as estimating voter propensities/outcomes for certain combinations of age by gender by race/origin combinations.The tables have been developed using the ProximityOne Modeler2 software (more below).

ZIP Code Area 89104

  View developed with CV XE GIS.

ZIP Code 89104 is located in Clark County, NV (32003).

More detailed demographic-economic data for all ZIP codes are available in these interactive tables: general demographics, social characteristics, economic characteristics and housing characteristics. See the this guide for more information about ZIP code data resources.

Data presented in the tables below are based on the Census-sourced single year of age demographics for sub-county areas from the Census 2010 Summary File 1 (SF1). The Census 2010 SF1 "PCT012" (PCT: Population Census Tract and higher geography) tables provide single year of age by gender by race/origin population data for U.S. national scope census tract, ZIP code area and higher level geography. See more about the content and structure of the PCT012 tables.

Data shown in the tables are also available structured as Excel files and with data presented as percentages in addition to population values. The data are also available as datasets organized in alternative structures to facilitate other types of analysis (e.g., a set of ZIP Code areas with each record corresponding to one ZIP Code area). The same scope of subject matter is available for current year estimates and projections to 2020. Contact us (888.364.7656) for more information about these options.

ProximityOne uses these data to develop census tract, ZIP code area and county-up geography SYOA estimates and projections to 2020. See more about 5-year projections.

Table 1. Single Year of Age by Race/Origin; 2010; Area: 89104 -- scroll section
AgeTotalWhite
alone		Black
alone		AIAN /1
alone		Asian
alone		NHOPI /2
alone		Other race
alone		Two or
more races		Hispanic
any race
Total population 39,909 21,779 2,965 382 2,298 239 10,446 1,800 21,344
Age 0 531 233 44 6 16 3 188 41 394
Age 1 601 281 43 4 13 4 216 40 445
Age 2 586 264 35 2 17 5 221 42 435
Age 3 663 263 62 5 13 3 270 47 504
Age 4 566 247 39 5 17 2 217 39 432
Age 5 537 241 45 6 15 7 175 48 396
Age 6 560 252 35 6 22 2 216 27 413
Age 7 514 212 40 6 14 4 205 33 394
Age 8 544 219 44 3 18 3 218 39 416
Age 9 546 237 40 8 18 8 194 41 411
Age 10 524 236 31 1 23 2 200 31 385
Age 11 526 226 34 1 33 5 193 34 387
Age 12 511 238 34 5 25 5 173 31 363
Age 13 482 207 23 3 26 4 191 28 378
Age 14 557 248 49 5 18 3 206 28 399
Age 15 554 245 40 8 21 2 197 41 406
Age 16 602 252 44 4 28 8 225 41 424
Age 17 517 237 34 3 27 4 183 29 357
Age 18 579 264 50 8 30 3 191 33 392
Age 19 555 244 47 6 29 5 195 29 373
Age 20 566 259 50 6 31 5 184 31 370
Age 21 547 249 40 9 33 1 187 28 350
Age 22 534 234 42 4 22 4 197 31 346
Age 23 529 251 43 6 21 3 183 22 352
Age 24 560 249 37 5 28 6 207 28 374
Age 25 531 226 39 8 30 0 210 18 366
Age 26 511 257 40 2 16 5 171 20 318
Age 27 590 276 57 6 26 2 194 29 366
Age 28 554 255 41 5 27 3 202 21 357
Age 29 499 203 42 8 28 4 188 26 326
Age 30 584 276 34 8 28 6 205 27 384
Age 31 486 243 40 7 23 5 151 17 294
Age 32 511 260 30 4 13 2 181 21 340
Age 33 508 238 33 3 31 1 171 31 319
Age 34 524 245 43 6 20 6 178 26 340
Age 35 547 269 32 7 28 2 183 26 354
Age 36 495 256 30 6 39 4 142 18 313
Age 37 535 285 41 6 33 1 148 21 328
Age 38 547 286 40 7 30 2 167 15 346
Age 39 589 308 45 6 21 2 186 21 363
Age 40 654 335 54 8 42 2 195 18 395
Age 41 522 282 45 2 37 3 132 21 301
Age 42 508 279 31 4 32 1 137 24 296
Age 43 520 283 40 4 22 5 147 19 273
Age 44 593 323 45 7 38 5 153 22 330
Age 45 647 347 47 6 32 1 189 25 364
Age 46 542 291 42 2 47 2 128 30 268
Age 47 605 359 49 3 47 3 120 24 264
Age 48 609 361 41 10 46 1 122 28 265
Age 49 566 321 56 5 44 7 106 27 234
Age 50 564 319 66 7 32 6 112 22 237
Age 51 517 298 44 7 52 1 93 22 197
Age 52 528 315 39 9 42 3 94 26 200
Age 53 522 335 42 9 31 4 86 15 183
Age 54 513 329 38 9 43 2 81 11 178
Age 55 545 353 40 4 53 1 72 22 174
Age 56 500 313 47 8 47 2 65 18 146
Age 57 529 337 38 9 49 5 69 22 155
Age 58 470 306 49 2 42 1 60 10 151
Age 59 491 324 46 2 35 2 64 18 137
Age 60 522 357 36 3 56 0 52 18 130
Age 61 430 301 25 3 39 4 43 15 109
Age 62 494 354 33 3 41 1 44 18 117
Age 63 439 318 19 4 48 4 38 8 107
Age 64 382 274 33 3 25 3 32 12 95
Age 65 358 260 26 3 26 4 31 8 101
Age 66 378 296 22 2 23 1 22 12 88
Age 67 371 280 29 3 22 1 28 8 90
Age 68 309 238 15 2 26 2 20 6 61
Age 69 300 221 21 1 16 2 31 8 88
Age 70 289 213 17 4 27 0 23 5 68
Age 71 228 175 15 2 17 3 14 2 39
Age 72 250 183 26 1 18 1 13 8 64
Age 73 229 172 16 1 19 0 13 8 56
Age 74 201 149 13 4 16 0 13 6 45
Age 75 187 147 15 1 14 0 7 3 40
Age 76 182 142 12 0 9 1 14 4 32
Age 77 195 141 19 2 11 2 15 5 37
Age 78 153 115 8 0 15 2 10 3 34
Age 79 146 117 5 0 15 1 8 0 31
Age 80 170 136 9 1 7 0 9 8 27
Age 81 125 99 7 1 14 0 2 2 12
Age 82 134 114 11 0 5 2 0 2 5
Age 83 94 83 3 1 4 0 2 1 11
Age 84 115 90 7 2 9 0 5 2 21
Age 85 109 93 3 1 3 1 7 1 20
Age 86 73 65 1 0 2 1 3 1 13
Age 87 61 54 2 0 0 0 2 3 8
Age 88 59 50 1 1 3 0 4 0 7
Age 89 39 34 3 0 0 0 2 0 6
Age 90 46 41 0 1 2 0 2 0 7
Age 91 32 30 1 0 0 0 1 0 5
Age 92 26 25 0 0 0 0 1 0 4
Age 93 9 8 0 1 0 0 0 0 2
Age 94 8 8 0 0 0 0 0 0 0
Age 95 9 8 0 0 1 0 0 0 1
Age 96 1 0 0 0 0 0 1 0 1
Age 97 5 3 1 0 1 0 0 0 1
Age 98 1 1 0 0 0 0 0 0 0
Age 99 0 0 0 0 0 0 0 0 0
Age 100-104 3 3 0 0 0 0 0 0 3
Age 105-110 0 0 0 0 0 0 0 0 0
Age 110 up 0 0 0 0 0 0 0 0 0

  1/ AIAN: American Indian/Alaska Native
  2/ NHOPI: Native Hawaiian/Other Pacific Islander

Table 2. Age by Race/Origin; Age Groups; 2010; Area: 89104
AgeTotalWhite
alone		Black
alone		AIAN /1
alone		Asian
alone		NHOPI /2
alone		Other race
alone		Two or
more races		Hispanic
any race
Total population 39,909 21,779 2,965 382 2,298 239 10,446 1,800 21,344
Age 0-4 1,718 778 122 12 46 12 625 123 1,274
Age 5-9 2,840 1,215 221 28 81 18 1,083 194 2,139
Age 10-14 2,651 1,156 183 18 117 23 978 176 1,962
Age 15-19 2,712 1,189 190 23 120 21 1,002 167 1,964
Age 20-24 2,781 1,250 229 33 145 18 954 152 1,831
Age 25-29 2,721 1,259 216 27 121 16 965 117 1,776
Age 30-34 2,634 1,237 187 32 119 20 927 112 1,701
Age 35-39 2,609 1,293 179 28 151 14 822 122 1,654
Age 40-44 2,820 1,490 215 27 162 10 817 99 1,701
Age 45-49 2,907 1,603 223 22 186 16 737 120 1,499
Age 50-54 2,784 1,614 246 38 216 18 527 125 1,133
Age 55-59 2,609 1,667 205 39 223 14 373 88 836
Age 60-64 2,407 1,642 189 13 213 8 263 79 644
Age 65-69 1,928 1,428 129 15 144 13 151 48 481
Age 70-74 1,376 1,030 94 10 104 8 101 29 320
Age 75-79 994 751 75 8 69 3 62 26 210
Age 80-84 728 581 40 2 56 5 29 15 109
Age 85 up 690 596 22 7 25 2 30 8 110

  1/ AIAN: American Indian/Alaska Native
  2/ NHOPI: Native Hawaiian/Other Pacific Islander

Modeler2 Software
These tables have been developed using the ProximityOne Modeler2 software. Modeler2 is also used to create demographic-economic estimates and projections at the sub-county geographic levels including census tracts and ZIP code areas. Annual estimates and projections are developed for 2010 through 2020 by single year of age, and for age groups, by census tract and ZIP code area.

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ProximityOne develops geographic-demographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our software, data and methodologies to analyze their own data integrated with other data. Follow ProximityOne on Twitter at www.twitter.com/proximityone. Contact ProximityOne (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.

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