Misc
This Giant Map Shows All the Metropolitan Areas in the U.S.
This Giant Map Shows All the Metropolitan Areas in the U.S.
The United States is the third most populous country in the world, made up of close to 20,000 cities and towns, and 333 million individuals.
Dividing these population clusters into a coherent framework of statistical areas is no small feat, and the U.S. Census Bureau’s latest map shows just how complex of a task it is.
This enormous map—which covers the entire country, including Puerto Rico—includes 392 metropolitan statistical areas and 547 micropolitan statistical areas.
For reference, here are all the current metropolitan statistical areas in the United States, organized by population:
Rank | Metropolitan statistical area | Population (2020) | Change since 2010 |
---|---|---|---|
1 | New York-Newark-Jersey City, NY-NJ-PA MSA | 20,140,470 | 6.58% |
2 | Los Angeles-Long Beach-Anaheim, CA MSA | 13,200,998 | 2.90% |
3 | Chicago-Naperville-Elgin, IL-IN-WI MSA | 9,618,502 | 1.66% |
4 | Dallas-Fort Worth-Arlington, TX MSA | 7,637,387 | 19.96% |
5 | Houston-The Woodlands-Sugar Land, TX MSA | 7,122,240 | 20.30% |
6 | Washington-Arlington-Alexandria, DC-VA-MD-WV MSA | 6,385,162 | 13.02% |
7 | Philadelphia-Camden-Wilmington, PA-NJ-DE-MD MSA | 6,245,051 | 4.69% |
8 | Miami-Fort Lauderdale-West Palm Beach, FL MSA | 6,138,333 | 10.31% |
9 | Atlanta-Sandy Springs-Alpharetta, GA MSA | 6,089,815 | 15.19% |
10 | Boston-Cambridge-Newton, MA-NH MSA | 4,941,632 | 8.55% |
11 | Phoenix-Mesa-Chandler, AZ MSA | 4,845,832 | 15.57% |
12 | San Francisco-Oakland-Berkeley, CA MSA | 4,749,008 | 9.54% |
13 | Riverside-San Bernardino-Ontario, CA MSA | 4,599,839 | 8.88% |
14 | Detroit–Warren–Dearborn, MI MSA | 4,392,041 | 2.23% |
15 | Seattle-Tacoma-Bellevue, WA MSA | 4,018,762 | 16.83% |
16 | Minneapolis-St. Paul-Bloomington, MN-WI MSA | 3,690,261 | 10.26% |
17 | San Diego-Chula Vista-Carlsbad, CA MSA | 3,298,634 | 6.57% |
18 | Tampa-St. Petersburg-Clearwater, FL MSA | 3,175,275 | 14.09% |
19 | Denver-Aurora-Lakewood, CO MSA | 2,963,821 | 16.53% |
20 | Baltimore-Columbia-Towson, MD MSA | 2,844,510 | 4.94% |
21 | St. Louis, MO-IL MSA | 2,820,253 | 1.17% |
22 | Orlando-Kissimmee-Sanford, FL MSA | 2,673,376 | 25.25% |
23 | Charlotte-Concord-Gastonia, NC-SC MSA | 2,660,329 | 18.56% |
24 | San Antonio-New Braunfels, TX MSA | 2,558,143 | 19.40% |
25 | Portland-Vancouver-Hillsboro, OR-WA MSA | 2,512,859 | 12.89% |
26 | Sacramento-Roseville-Folsom, CA MSA | 2,397,382 | 11.55% |
27 | Pittsburgh, PA MSA | 2,370,930 | 0.62% |
28 | Austin-Round Rock-Georgetown, TX MSA | 2,283,371 | 33.04% |
29 | Las Vegas-Henderson-Paradise, NV MSA | 2,265,461 | 16.10% |
30 | Cincinnati, OH-KY-IN MSA | 2,256,884 | 5.58% |
31 | Kansas City, MO-KS MSA | 2,192,035 | 9.09% |
32 | Columbus, OH MSA | 2,138,926 | 12.46% |
33 | Indianapolis-Carmel-Anderson, IN MSA | 2,111,040 | 11.82% |
34 | Cleveland-Elyria, OH MSA | 2,088,251 | 0.53% |
35 | San Juan-Bayamón-Caguas, PR Metropolitan Statistical Area | 2,002,906 | -14.77% |
36 | San Jose-Sunnyvale-Santa Clara, CA MSA | 2,000,468 | 8.90% |
37 | Nashville-Davidson–Murfreesboro–Franklin, TN MSA | 1,989,519 | 20.86% |
38 | Virginia Beach-Norfolk-Newport News, VA-NC MSA | 1,799,674 | 5.00% |
39 | Providence-Warwick, RI-MA MSA | 1,676,579 | 4.73% |
40 | Jacksonville, FL MSA | 1,605,848 | 19.34% |
41 | Milwaukee-Waukesha, WI MSA | 1,574,731 | 1.21% |
42 | Oklahoma City, OK MSA | 1,425,695 | 13.78% |
43 | Raleigh-Cary, NC MSA | 1,413,982 | 25.08% |
44 | Memphis, TN-MS-AR MSA | 1,337,779 | 1.65% |
45 | Richmond, VA MSA | 1,314,434 | 10.78% |
46 | Louisville/Jefferson County, KY-IN MSA | 1,285,439 | 6.88% |
47 | New Orleans-Metairie, LA MSA | 1,271,845 | 6.89% |
48 | Salt Lake City, UT MSA | 1,257,936 | 15.63% |
49 | Hartford-East Hartford-Middletown, CT MSA | 1,213,531 | 0.09% |
50 | Buffalo-Niagara Falls, NY MSA | 1,166,902 | 2.76% |
51 | Birmingham-Hoover, AL MSA | 1,115,289 | 5.11% |
52 | Rochester, NY MSA | 1,090,135 | 0.97% |
53 | Grand Rapids-Kentwood, MI MSA | 1,087,592 | 9.45% |
54 | Tucson, AZ MSA | 1,043,433 | 6.44% |
55 | Urban Honolulu, HI MSA | 1,016,508 | 6.64% |
56 | Tulsa, OK MSA | 1,015,331 | 8.30% |
57 | Fresno, CA MSA | 1,008,654 | 8.40% |
58 | Worcester, MA-CT MSA | 978,529 | 6.71% |
59 | Omaha-Council Bluffs, NE-IA MSA | 967,604 | 11.82% |
60 | Bridgeport-Stamford-Norwalk, CT MSA | 957,419 | 4.43% |
61 | Greenville-Anderson, SC MSA | 928,195 | 12.63% |
62 | Albuquerque, NM MSA | 916,528 | 3.32% |
63 | Bakersfield, CA MSA | 909,235 | 8.29% |
64 | Albany-Schenectady-Troy, NY MSA | 899,262 | 3.28% |
65 | Knoxville, TN MSA | 879,773 | 7.96% |
66 | McAllen-Edinburg-Mission, TX MSA | 870,781 | 12.39% |
67 | Baton Rouge, LA MSA | 870,569 | 5.41% |
68 | El Paso, TX MSA | 868,859 | 8.05% |
69 | New Haven-Milford, CT MSA | 864,835 | 0.27% |
70 | Allentown-Bethlehem-Easton, PA-NJ MSA | 861,889 | 4.96% |
71 | Oxnard-Thousand Oaks-Ventura, CA MSA | 843,843 | 2.49% |
72 | North Port-Sarasota-Bradenton, FL MSA | 833,716 | 18.72% |
73 | Columbia, SC MSA | 829,470 | 8.06% |
74 | Dayton-Kettering, OH MSA | 814,049 | 1.85% |
75 | Charleston-North Charleston, SC MSA | 799,636 | 20.32% |
76 | Stockton, CA MSA | 779,233 | 13.71% |
77 | Greensboro-High Point, NC MSA | 776,566 | 7.29% |
78 | Boise City, ID MSA | 764,718 | 24.03% |
79 | Cape Coral-Fort Myers, FL MSA | 760,822 | 22.96% |
80 | Colorado Springs, CO MSA | 755,105 | 16.96% |
81 | Little Rock-North Little Rock-Conway, AR MSA | 748,031 | 6.90% |
82 | Lakeland-Winter Haven, FL MSA | 725,046 | 20.42% |
83 | Des Moines-West Des Moines, IA MSA | 709,466 | 16.98% |
84 | Akron, OH MSA | 702,219 | -0.14% |
85 | Springfield, MA MSA | 699,162 | 0.90% |
86 | Poughkeepsie-Newburgh-Middletown, NY MSA | 697,221 | 4.02% |
87 | Ogden-Clearfield, UT MSA | 694,863 | 16.36% |
88 | Madison, WI MSA | 680,796 | 12.45% |
89 | Winston-Salem, NC MSA | 675,966 | 5.52% |
90 | Provo-Orem, UT MSA | 671,185 | 27.41% |
91 | Deltona-Daytona Beach-Ormond Beach, FL MSA | 668,921 | 13.32% |
92 | Syracuse, NY MSA | 662,057 | -0.08% |
93 | Durham-Chapel Hill, NC MSA | 649,903 | 15.18% |
94 | Wichita, KS MSA | 647,610 | 3.94% |
95 | Toledo, OH MSA | 646,604 | -0.74% |
96 | Augusta-Richmond County, GA-SC MSA | 611,000 | 8.17% |
97 | Palm Bay-Melbourne-Titusville, FL MSA | 606,612 | 11.64% |
98 | Jackson, MS MSA | 591,978 | 0.97% |
99 | Harrisburg-Carlisle, PA MSA | 591,712 | 7.69% |
100 | Spokane-Spokane Valley, WA MSA | 585,784 | 13.80% |
101 | Scranton–Wilkes-Barre, PA MSA | 567,559 | 0.70% |
102 | Chattanooga, TN-GA MSA | 562,647 | 6.53% |
103 | Lancaster, PA MSA | 552,984 | 6.46% |
104 | Modesto, CA MSA | 552,878 | 7.47% |
105 | Portland-South Portland, ME MSA | 551,740 | 7.32% |
106 | Fayetteville-Springdale-Rogers, AR MSA | 546,725 | 24.22% |
107 | Lansing-East Lansing, MI MSA | 541,297 | 1.24% |
108 | Youngstown-Warren-Boardman, OH-PA MSA | 541,243 | -4.34% |
109 | Fayetteville, NC MSA | 520,378 | 8.17% |
110 | Lexington-Fayette, KY MSA | 516,811 | 9.47% |
111 | Pensacola-Ferry Pass-Brent, FL MSA | 509,905 | 13.57% |
112 | Huntsville, AL MSA | 491,723 | 17.75% |
113 | Reno, NV MSA | 490,596 | 15.32% |
114 | Santa Rosa-Petaluma, CA MSA | 488,863 | 1.03% |
115 | Myrtle Beach-Conway-North Myrtle Beach, SC-NC MSA | 487,722 | 29.46% |
116 | Port St. Lucie, FL MSA | 487,657 | 14.98% |
117 | Lafayette, LA MSA | 478,384 | 2.49% |
118 | Springfield, MO MSA | 475,432 | 8.87% |
119 | Killeen-Temple, TX MSA | 475,367 | 17.29% |
120 | Visalia, CA MSA | 473,117 | 7.00% |
121 | Asheville, NC MSA | 469,015 | 10.39% |
122 | York-Hanover, PA MSA | 456,438 | 4.94% |
123 | Vallejo, CA MSA | 453,491 | 9.71% |
124 | Santa Maria-Santa Barbara, CA MSA | 448,229 | 5.74% |
125 | Salinas, CA MSA | 439,035 | 5.78% |
126 | Salem, OR MSA | 433,353 | 10.91% |
127 | Mobile, AL MSA | 430,197 | -0.09% |
128 | Reading, PA MSA | 428,849 | 4.23% |
129 | Manchester-Nashua, NH MSA | 422,937 | 5.54% |
130 | Corpus Christi, TX MSA | 421,933 | 4.17% |
131 | Brownsville-Harlingen, TX MSA | 421,017 | 3.64% |
132 | Fort Wayne, IN MSA | 419,601 | 7.97% |
133 | Salisbury, MD-DE MSA | 418,046 | 11.84% |
134 | Gulfport-Biloxi, MS MSA | 416,259 | 7.15% |
135 | Flint, MI MSA | 406,211 | -4.60% |
136 | Savannah, GA MSA | 404,798 | 16.45% |
137 | Peoria, IL MSA | 402,391 | -3.33% |
138 | Canton-Massillon, OH MSA | 401,574 | -0.70% |
139 | Anchorage, AK MSA | 398,328 | 4.60% |
140 | Beaumont-Port Arthur, TX MSA | 397,565 | 2.27% |
141 | Shreveport-Bossier City, LA MSA | 393,406 | -1.30% |
142 | Trenton-Princeton, NJ MSA | 387,340 | 5.68% |
143 | Montgomery, AL MSA | 386,047 | 3.07% |
144 | Davenport-Moline-Rock Island, IA-IL MSA | 384,324 | 1.22% |
145 | Tallahassee, FL MSA | 384,298 | 4.60% |
146 | Eugene-Springfield, OR MSA | 382,971 | 8.89% |
147 | Ocala, FL MSA | 375,908 | 13.47% |
148 | Naples-Marco Island, FL MSA | 375,752 | 16.87% |
149 | Ann Arbor, MI MSA | 372,258 | 7.97% |
150 | Hickory-Lenoir-Morganton, NC MSA | 365,276 | -0.06% |
151 | Huntington-Ashland, WV-KY-OH MSA | 359,862 | -2.98% |
152 | Fort Collins, CO MSA | 359,066 | 19.84% |
153 | Lincoln, NE MSA | 340,217 | 12.60% |
154 | Gainesville, FL MSA | 339,247 | 11.20% |
155 | Rockford, IL MSA | 338,798 | -3.04% |
156 | Boulder, CO MSA | 330,758 | 12.29% |
157 | Greeley, CO MSA | 328,981 | 30.12% |
158 | Columbus, GA-AL MSA | 328,883 | 6.85% |
159 | Green Bay, WI MSA | 328,268 | 7.19% |
160 | Spartanburg, SC MSA | 327,997 | 15.37% |
161 | South Bend-Mishawaka, IN-MI MSA | 324,501 | 1.65% |
162 | Lubbock, TX MSA | 321,368 | 10.51% |
163 | Clarksville, TN-KY MSA | 320,535 | 17.01% |
164 | Roanoke, VA MSA | 315,251 | 2.12% |
165 | Evansville, IN-KY MSA | 314,049 | 0.80% |
166 | Kingsport-Bristol, TN-VA MSA | 307,614 | -0.62% |
167 | Kennewick-Richland, WA MSA | 303,622 | 19.85% |
168 | Olympia-Lacey-Tumwater, WA MSA | 294,793 | 16.86% |
169 | Hagerstown-Martinsburg, MD-WV MSA | 293,844 | 9.18% |
170 | Utica-Rome, NY MSA | 292,264 | -2.38% |
171 | Duluth, MN-WI MSA | 291,638 | 0.34% |
172 | Crestview-Fort Walton Beach-Destin, FL MSA | 286,973 | 21.67% |
173 | Longview, TX MSA | 286,184 | 2.21% |
174 | Aguadilla-Isabela, PR Metropolitan Statistical Area | 286,064 | -15.72% |
175 | Wilmington, NC MSA | 285,905 | 12.17% |
176 | San Luis Obispo-Paso Robles, CA MSA | 282,424 | 4.74% |
177 | Merced, CA MSA | 281,202 | 9.93% |
178 | Waco, TX MSA | 277,547 | 9.80% |
179 | Sioux Falls, SD MSA | 276,730 | 21.23% |
180 | Cedar Rapids, IA MSA | 276,520 | 7.20% |
181 | Bremerton-Silverdale-Port Orchard, WA MSA | 275,611 | 9.75% |
182 | Atlantic City-Hammonton, NJ MSA | 274,534 | -0.01% |
183 | Erie, PA MSA | 270,876 | -3.45% |
184 | Santa Cruz-Watsonville, CA MSA | 270,861 | 3.23% |
185 | Amarillo, TX MSA | 268,761 | 6.68% |
186 | Tuscaloosa, AL MSA | 268,674 | 12.32% |
187 | Norwich-New London, CT MSA | 268,555 | -2.01% |
188 | College Station-Bryan, TX MSA | 268,248 | 17.31% |
189 | Laredo, TX MSA | 267,114 | 6.72% |
190 | Kalamazoo-Portage, MI MSA | 261,670 | 4.53% |
191 | Lynchburg, VA MSA | 261,593 | 3.55% |
192 | Charleston, WV MSA | 258,859 | -6.89% |
193 | Yakima, WA MSA | 256,728 | 5.55% |
194 | Fargo, ND-MN MSA | 249,843 | 19.67% |
195 | Binghamton, NY MSA | 247,138 | -1.82% |
196 | Fort Smith, AR-OK MSA | 244,310 | -1.57% |
197 | Appleton, WI MSA | 243,147 | 7.75% |
198 | Prescott Valley-Prescott, AZ MSA | 236,209 | 11.93% |
199 | Macon-Bibb County, GA MSA | 233,802 | 0.65% |
200 | Tyler, TX MSA | 233,479 | 11.33% |
201 | Topeka, KS MSA | 233,152 | -0.31% |
202 | Daphne-Fairhope-Foley, AL MSA | 231,767 | 27.16% |
203 | Barnstable Town, MA MSA | 228,996 | 6.07% |
204 | Bellingham, WA MSA | 226,847 | 12.78% |
205 | Rochester, MN MSA | 226,329 | 9.40% |
206 | Burlington-South Burlington, VT MSA | 225,562 | 6.77% |
207 | Lafayette-West Lafayette, IN MSA | 223,716 | 6.38% |
208 | Medford, OR MSA | 223,259 | 9.87% |
209 | Champaign-Urbana, IL MSA | 222,538 | 2.17% |
210 | Lake Charles, LA MSA | 222,402 | 11.42% |
211 | Charlottesville, VA MSA | 221,524 | 9.91% |
212 | Las Cruces, NM MSA | 219,561 | 4.94% |
213 | Hilton Head Island-Bluffton-Beaufort, SC MSA | 215,908 | 15.45% |
214 | Athens-Clarke County, GA MSA | 215,415 | 11.88% |
215 | Lake Havasu City-Kingman, AZ MSA | 213,267 | 6.53% |
216 | Chico, CA MSA | 211,632 | -3.80% |
217 | Ponce, PR Metropolitan Statistical Area | 211,465 | -19.48% |
218 | Columbia, MO MSA | 210,864 | 10.76% |
219 | Springfield, IL MSA | 208,640 | -0.73% |
220 | Johnson City, TN MSA | 207,285 | 4.31% |
221 | Houma-Thibodaux, LA MSA | 207,137 | -0.50% |
222 | Monroe, LA MSA | 207,104 | 1.31% |
223 | Elkhart-Goshen, IN MSA | 207,047 | 4.80% |
224 | Jacksonville, NC MSA | 204,576 | 15.08% |
225 | Yuma, AZ MSA | 203,881 | 4.15% |
226 | Gainesville, GA MSA | 203,136 | 13.05% |
227 | Florence, SC MSA | 199,964 | -2.73% |
228 | St. Cloud, MN MSA | 199,671 | 5.59% |
229 | Bend, OR MSA | 198,253 | 25.69% |
230 | Racine, WI MSA | 197,727 | 1.19% |
231 | Warner Robins, GA MSA | 191,614 | 14.33% |
232 | Saginaw, MI MSA | 190,124 | -5.02% |
233 | Punta Gorda, FL MSA | 186,847 | 16.80% |
234 | Terre Haute, IN MSA | 185,031 | -2.49% |
235 | Billings, MT MSA | 184,167 | 10.17% |
236 | Redding, CA MSA | 182,155 | 2.78% |
237 | Dover, DE MSA | 181,851 | 12.04% |
238 | Kingston, NY MSA | 181,851 | -0.35% |
239 | Joplin, MO MSA | 181,409 | 3.36% |
240 | Yuba City, CA MSA | 181,208 | 8.58% |
241 | Jackson, TN MSA | 180,504 | 0.45% |
242 | St. George, UT MSA | 180,279 | 30.53% |
243 | El Centro, CA MSA | 179,702 | 2.96% |
244 | Bowling Green, KY MSA | 179,639 | 13.27% |
245 | Abilene, TX MSA | 176,579 | 6.85% |
246 | Muskegon, MI MSA | 175,824 | 2.11% |
247 | Iowa City, IA MSA | 175,419 | 14.96% |
248 | Midland, TX MSA | 175,220 | 23.68% |
249 | Panama City, FL MSA | 175,216 | 3.77% |
250 | Auburn-Opelika, AL MSA | 174,241 | 24.24% |
251 | Arecibo, PR Metropolitan Statistical Area | 173,218 | -13.16% |
252 | Hattiesburg, MS MSA | 172,231 | 6.05% |
253 | Eau Claire, WI MSA | 172,007 | 6.74% |
254 | Oshkosh-Neenah, WI MSA | 171,730 | 2.84% |
255 | Burlington, NC MSA | 171,415 | 13.42% |
256 | Coeur d'Alene, ID MSA | 171,362 | 23.73% |
257 | Bloomington, IL MSA | 170,954 | 0.81% |
258 | Greenville, NC MSA | 170,243 | 1.25% |
259 | Waterloo-Cedar Falls, IA MSA | 168,461 | 0.38% |
260 | East Stroudsburg, PA MSA | 168,327 | -0.89% |
261 | Pueblo, CO MSA | 168,162 | 5.72% |
262 | Wausau-Weston, WI MSA | 166,428 | 2.22% |
263 | Blacksburg-Christiansburg, VA MSA | 166,378 | 2.10% |
264 | Odessa, TX MSA | 165,171 | 20.45% |
265 | Kahului-Wailuku-Lahaina, HI MSA | 164,754 | 6.41% |
266 | Janesville-Beloit, WI MSA | 163,687 | 2.09% |
267 | Bloomington, IN MSA | 161,039 | 0.93% |
268 | Jackson, MI MSA | 160,366 | 0.07% |
269 | Sebastian-Vero Beach, FL MSA | 159,788 | 15.76% |
270 | State College, PA MSA | 158,172 | 2.72% |
271 | Idaho Falls, ID MSA | 157,429 | 18.13% |
272 | Decatur, AL MSA | 156,494 | 1.73% |
273 | Madera, CA MSA | 156,255 | 3.57% |
274 | Chambersburg-Waynesboro, PA MSA | 155,932 | 4.22% |
275 | Grand Junction, CO MSA | 155,703 | 6.12% |
276 | Elizabethtown-Fort Knox, KY MSA | 155,572 | 4.88% |
277 | Santa Fe, NM MSA | 154,823 | 7.39% |
278 | Monroe, MI MSA | 154,809 | 1.83% |
279 | Niles, MI MSA | 154,316 | -1.59% |
280 | Vineland-Bridgeton, NJ MSA | 154,152 | -1.75% |
281 | Homosassa Springs, FL MSA | 153,843 | 8.93% |
282 | Hanford-Corcoran, CA MSA | 152,486 | -0.32% |
283 | Bangor, ME MSA | 152,199 | -1.12% |
284 | Alexandria, LA MSA | 152,192 | -1.12% |
285 | Dothan, AL MSA | 151,007 | 3.69% |
286 | Florence-Muscle Shoals, AL MSA | 150,791 | 2.48% |
287 | Jefferson City, MO MSA | 150,309 | 0.34% |
288 | Sioux City, IA-NE-SD MSA | 149,940 | 4.43% |
289 | Albany, GA MSA | 148,922 | -3.21% |
290 | Wichita Falls, TX MSA | 148,128 | -2.10% |
291 | Valdosta, GA MSA | 148,126 | 6.12% |
292 | Texarkana, TX-AR MSA | 147,519 | -1.13% |
293 | Logan, UT-ID MSA | 147,348 | 17.46% |
294 | Flagstaff, AZ MSA | 145,101 | 7.95% |
295 | Rocky Mount, NC MSA | 143,870 | -5.59% |
296 | Lebanon, PA MSA | 143,257 | 7.25% |
297 | Dalton, GA MSA | 142,837 | 0.43% |
298 | Morristown, TN MSA | 142,709 | 4.47% |
299 | Winchester, VA-WV MSA | 142,632 | 11.02% |
300 | Morgantown, WV MSA | 140,038 | 7.96% |
301 | La Crosse-Onalaska, WI-MN MSA | 139,627 | 4.46% |
302 | Wheeling, WV-OH MSA | 139,513 | -5.70% |
303 | Rapid City, SD MSA | 139,074 | 10.04% |
304 | Napa, CA MSA | 138,019 | 1.12% |
305 | Sumter, SC MSA | 136,700 | -4.02% |
306 | Springfield, OH MSA | 136,001 | -1.69% |
307 | Harrisonburg, VA MSA | 135,571 | 8.26% |
308 | Sherman-Denison, TX MSA | 135,543 | 12.13% |
309 | Battle Creek, MI MSA | 134,310 | -1.35% |
310 | Jonesboro, AR MSA | 134,196 | 10.88% |
311 | Manhattan, KS MSA | 134,046 | 5.48% |
312 | Bismarck, ND MSA | 133,626 | 20.79% |
313 | Johnstown, PA MSA | 133,472 | -7.10% |
314 | Carbondale-Marion, IL MSA | 133,435 | -4.11% |
315 | Hammond, LA MSA | 133,157 | 9.96% |
316 | The Villages, FL MSA | 129,752 | 38.89% |
317 | Mount Vernon-Anacortes, WA MSA | 129,523 | 10.80% |
318 | Pittsfield, MA MSA | 129,026 | -1.67% |
319 | Albany-Lebanon, OR MSA | 128,610 | 10.23% |
320 | Glens Falls, NY MSA | 127,039 | -1.46% |
321 | Lawton, OK MSA | 126,652 | -2.79% |
322 | Cleveland, TN MSA | 126,164 | 8.96% |
323 | Sierra Vista-Douglas, AZ MSA | 125,447 | -4.49% |
324 | Staunton, VA MSA | 125,433 | 5.85% |
325 | Ames, IA MSA | 125,252 | 8.12% |
326 | Mansfield, OH MSA | 124,936 | 0.37% |
327 | San Angelo, TX MSA | 122,888 | 8.78% |
328 | Altoona, PA MSA | 122,822 | -3.36% |
329 | New Bern, NC MSA | 122,168 | -3.65% |
330 | Wenatchee, WA MSA | 122,012 | 10.04% |
331 | Farmington, NM MSA | 121,661 | -6.45% |
332 | Owensboro, KY MSA | 121,559 | 5.93% |
333 | St. Joseph, MO-KS MSA | 121,467 | -4.60% |
334 | San Germán, PR Metropolitan Statistical Area | 120,280 | -12.50% |
335 | Lawrence, KS MSA | 118,785 | 7.18% |
336 | Sheboygan, WI MSA | 118,034 | 2.19% |
337 | Missoula, MT MSA | 117,922 | 7.89% |
338 | Goldsboro, NC MSA | 117,333 | -4.31% |
339 | Weirton-Steubenville, WV-OH MSA | 116,903 | -6.07% |
340 | Watertown-Fort Drum, NY MSA | 116,721 | 0.42% |
341 | Anniston-Oxford, AL MSA | 116,441 | -1.80% |
342 | Beckley, WV MSA | 115,079 | -7.86% |
343 | Twin Falls, ID MSA | 114,283 | 14.74% |
344 | Williamsport, PA MSA | 114,188 | -1.66% |
345 | California-Lexington Park, MD MSA | 113,777 | 8.20% |
346 | Brunswick, GA MSA | 113,495 | 1.00% |
347 | Michigan City-La Porte, IN MSA | 112,417 | 0.85% |
348 | Muncie, IN MSA | 111,903 | -4.90% |
349 | Lewiston-Auburn, ME MSA | 111,139 | 3.19% |
350 | Longview, WA MSA | 110,730 | 8.12% |
351 | Kankakee, IL MSA | 107,502 | -5.24% |
352 | Ithaca, NY MSA | 105,740 | 4.11% |
353 | Grand Forks, ND-MN MSA | 104,362 | 5.99% |
354 | Fond du Lac, WI MSA | 104,154 | 2.48% |
355 | Decatur, IL MSA | 103,998 | -6.11% |
356 | Bay City, MI MSA | 103,856 | -3.63% |
357 | Gettysburg, PA MSA | 103,852 | 2.41% |
358 | Mankato, MN MSA | 103,566 | 7.06% |
359 | Gadsden, AL MSA | 103,436 | -0.95% |
360 | Lima, OH MSA | 102,206 | -3.88% |
361 | Sebring-Avon Park, FL MSA | 101,235 | 2.48% |
362 | Cheyenne, WY MSA | 100,512 | 9.56% |
363 | Hot Springs, AR MSA | 100,180 | 4.33% |
364 | Dubuque, IA MSA | 99,266 | 5.99% |
365 | Rome, GA MSA | 98,584 | 2.35% |
366 | Victoria, TX MSA | 98,331 | 4.60% |
367 | Cape Girardeau, MO-IL MSA | 97,517 | 1.29% |
368 | Fairbanks, AK MSA | 95,655 | -1.97% |
369 | Ocean City, NJ MSA | 95,263 | -2.06% |
370 | Corvallis, OR MSA | 95,184 | 11.22% |
371 | Cumberland, MD-WV MSA | 95,044 | -7.99% |
372 | Pocatello, ID MSA | 94,896 | 4.68% |
373 | Mayagüez, PR Metropolitan Statistical Area | 93,412 | -19.62% |
374 | Parkersburg-Vienna, WV MSA | 89,490 | -3.43% |
375 | Grants Pass, OR MSA | 88,090 | 6.50% |
376 | Pine Bluff, AR MSA | 87,751 | -12.47% |
377 | Great Falls, MT MSA | 84,414 | 3.80% |
378 | Elmira, NY MSA | 84,148 | -5.27% |
379 | Yauco, PR Metropolitan Statistical Area | 84,112 | -21.63% |
380 | Kokomo, IN MSA | 83,658 | 1.09% |
381 | Midland, MI MSA | 83,494 | -0.16% |
382 | Bloomsburg-Berwick, PA MSA | 82,863 | -3.15% |
383 | Columbus, IN MSA | 82,208 | 7.05% |
384 | Hinesville, GA MSA | 81,424 | 4.50% |
385 | Casper, WY MSA | 79,955 | 5.97% |
386 | Grand Island, NE MSA | 77,038 | 5.93% |
387 | Danville, IL MSA | 74,188 | -9.11% |
388 | Guayama, PR Metropolitan Statistical Area | 72,240 | -14.22% |
389 | Lewiston, ID-WA MSA | 64,375 | 5.73% |
390 | Enid, OK MSA | 62,846 | 3.74% |
391 | Walla Walla, WA MSA | 62,584 | 6.47% |
392 | Carson City, NV MSA | 58,639 | 6.09% |
From Metro to Micro
The wide variety of population patterns around the country can make it tricky to divide regions up into uniform units. There are two main divisions to consider when viewing this map:
- Metropolitan Areas (metro areas) have at least one urban core area of at least 50,000 population. These are the largest population centers, sometimes encompassing many counties. In some instances, these metro areas are further subdivided into Metropolitan Divisions.
- Micropolitan Areas are the smallest areas measured on this map (indicated by a lighter shade of green). These smaller regions, which are generally located further away from large cities, have at least one urban core area of at least 10,000 but fewer than 50,000 people.
One thing to note about all of these definitions is that the cities in these regions must have significant ties to a neighboring region—usually in the form of commuting ties. This is what warrants binding adjacent counties into a measurable area.
Another unique layer of data on this map is the shading that indicates the actual urbanized area within metro areas. In the example of Atlanta-Sandy Springs-Alpharetta, it’s easy to see how urban sprawl has expanded the urban area into a number of neighboring counties.
With this context in mind, we’ll take a closer look at three points of interest on the map that show this concept at work with varying degrees of complexity.
Level One: The Central City
The Texas Triangle offers what is perhaps the most straightforward example of metro areas.
As seen above, Houston, Austin, and San Antonio anchor their respective regions, and surrounding counties are bundled into a metro area. The surrounding counties have all been identified as having ties to the central county, and, in some cases, the urban area has spread into the neighboring county over time.
Level Two: The City Cluster
The region anchored by Salt Lake City requires more thought to divide into statistical areas.
While there are a number of population centers in the area, including Salt Lake City, Provo, and Ogden, they all have enough of an economic “magnetic pull” to warrant splitting the region into distinct statistical areas.
Of course, regions are always evolving, and occasionally these areas are updated. Salt Lake City and Ogden were previously combined into a single metro area, but were separated in 2005.
Level Three: The Megaregion
New York City is the ultimate challenge for planners looking to categorize population centers into a neat and tidy statistical box.
For one, the contiguous urban area is massive, stretching from the west side of Long Island out to the east side of New Jersey. In addition to New York City itself, the metro area includes 19 other municipalities with over 100,000 people.
Next, NYC is an unparalleled economic magnet. Measuring commuting activity is a challenge because a wide variety of people visit the city for so many different reasons. The interconnectedness of the Northeast Megaregion also adds to the complexity.
New York-Newark-Jersey City is such a big pie to carve up, that four of the country’s 11 metro divisions (as indicated by the italicized text and dotted lines) occur in this one area.
Blurring the Lines
Population patterns are constantly changing across the country, so the next version of this map may have a number of changes on it. Our “straightforward” Texas Triangle example may become tougher to divide up as the population boom continues in the region.
Here’s how the population of U.S. countries changed over the past decade:
Further complicating matters is the rapid move to remote work and distributed teams. A key element of these census divisions are commuting ties. With work increasingly not bound by geographic limitations, it remains unclear how that trend will impact this type of statistical exercise in the future.
Misc
Visualizing Two Decades of Reported Hate Crimes in the U.S.
Hate crimes across the U.S. have been on the rise since 2014. Here’s a look at the most common types of offenses over the years.

Visualizing Two Decades of Reported Hate Crimes in the U.S.
Across the U.S., thousands of hate crimes are committed each year, with many different motivating biases.
In 2020 alone, more than 10,000 unique hate crime incidents were reported to the Federal Bureau of Investigation (FBI)—and it’s likely that thousands more were committed that didn’t get reported to law enforcement.
What are the most commonly reported motivating biases, and how have hate crime rates evolved over the years? This graphic uses data from the FBI to visualize two decades of reported hate crime incidents across America.
What is Considered a Hate Crime?
Before diving in, it’s important to determine what constitutes a hate crime.
According to the U.S. Department of Justice, a hate crime is a crime that’s “committed on the basis of the victim’s perceived or actual race, color, religion, national origin, sexual orientation, gender, gender identity, or disability.”
These types of crimes are a threat to society, as they have a broader impact on communities than other types of crimes do. This is because hate crimes can foster fear and intimidate large groups of people or marginalized communities, making them feel unwelcome, unsafe, or othered.
Hate Crimes on the Rise
Hate crimes have been rising across the U.S. in nearly every year since 2014. By 2020, reported crimes across America reached record-level highs not seen in over two decades.
Year | Number of Reported Incidents | % Change (y-o-y) |
---|---|---|
2001 | 9730 | 18.4% |
2002 | 7485 | -23.1% |
2003 | 7545 | 0.8% |
2004 | 7685 | 1.9% |
2005 | 7411 | -3.6% |
2006 | 7715 | 4.1% |
2007 | 7625 | -1.2% |
2008 | 8039 | 5.4% |
2009 | 6613 | -17.7% |
2010 | 6633 | 0.3% |
2011 | 6299 | -5.0% |
2012 | 6594 | 4.7% |
2013 | 6044 | -8.3% |
2014 | 5599 | -7.4% |
2015 | 5871 | 4.9% |
2016 | 6276 | 6.9% |
2017 | 7321 | 16.7% |
2018 | 7170 | -2.1% |
2019 | 7892 | 10.1% |
2020 | 10299 | 30.5% |
And sadly, these figures are likely a vast undercount. Law enforcement submit this data to the FBI of their own volition, and in 2020, thousands of agencies did not submit their crime statistics.
Race-Related Hate Crimes are Most Common
Historically, the most reported hate crimes in the U.S. are related to race. In 2020, about 66% of incidents were motivated by discrimination against the victim’s race or ethnicity.
Type of Bias | Total Number of Crimes (2020) | % of Total |
---|---|---|
Race/Ethnicity | 6793 | 66.0% |
Religion | 1626 | 15.8% |
Sexual Orientation | 1311 | 12.7% |
Other | 569 | 5.5% |
Total | 10299 | -- |
While race is the most commonly reported hate crime, incidents related to gender and gender identity are on the rise—in 2020, there was a 9% increase in gender-related incidents, and a 34% increase in gender identity-related incidents, compared to 2019 figures.
Science
Visualizing the Relationship Between Cancer and Lifespan
New research links mutation rates and lifespan. We visualize the data supporting this new framework for understanding cancer.

A Newfound Link Between Cancer and Aging?
A new study in 2022 reveals a thought-provoking relationship between how long animals live and how quickly their genetic codes mutate.
Cancer is a product of time and mutations, and so researchers investigated its onset and impact within 16 unique mammals. A new perspective on DNA mutation broadens our understanding of aging and cancer development—and how we might be able to control it.
Mutations, Aging, and Cancer: A Primer
Cancer is the uncontrolled growth of cells. It is not a pathogen that infects the body, but a normal body process gone wrong.
Cells divide and multiply in our bodies all the time. Sometimes, during DNA replication, tiny mistakes (called mutations) appear randomly within the genetic code. Our bodies have mechanisms to correct these errors, and for much of our youth we remain strong and healthy as a result of these corrective measures.
However, these protections weaken as we age. Developing cancer becomes more likely as mutations slip past our defenses and continue to multiply. The longer we live, the more mutations we carry, and the likelihood of them manifesting into cancer increases.
A Biological Conundrum
Since mutations can occur randomly, biologists expect larger lifeforms (those with more cells) to have greater chances of developing cancer than smaller lifeforms.
Strangely, no association exists.
It is one of biology’s biggest mysteries as to why massive creatures like whales or elephants rarely seem to experience cancer. This is called Peto’s Paradox. Even stranger: some smaller creatures, like the naked mole rat, are completely resistant to cancer.
This phenomenon motivates researchers to look into the genetics of naked mole rats and whales. And while we’ve discovered that special genetic bonuses (like extra tumor-suppressing genes) benefit these creatures, a pattern for cancer rates across all other species is still poorly understood.
Cancer May Be Closely Associated with Lifespan
Researchers at the Wellcome Sanger Institute report the first study to look at how mutation rates compare with animal lifespans.
Mutation rates are simply the speed at which species beget mutations. Mammals with shorter lifespans have average mutation rates that are very fast. A mouse undergoes nearly 800 mutations in each of its four short years on Earth. Mammals with longer lifespans have average mutation rates that are much slower. In humans (average lifespan of roughly 84 years), it comes to fewer than 50 mutations per year.
The study also compares the number of mutations at time of death with other traits, like body mass and lifespan. For example, a giraffe has roughly 40,000 times more cells than a mouse. Or a human lives 90 times longer than a mouse. What surprised researchers was that the number of mutations at time of death differed only by a factor of three.
Such small differentiation suggests there may be a total number of mutations a species can collect before it dies. Since the mammals reached this number at different speeds, finding ways to control the rate of mutations may help stall cancer development, set back aging, and prolong life.
The Future of Cancer Research
The findings in this study ignite new questions for understanding cancer.
Confirming that mutation rate and lifespan are strongly correlated needs comparison to lifeforms beyond mammals, like fishes, birds, and even plants.
It will also be necessary to understand what factors control mutation rates. The answer to this likely lies within the complexities of DNA. Geneticists and oncologists are continuing to investigate genetic curiosities like tumor-suppressing genes and how they might impact mutation rates.
Aging is likely to be a confluence of many issues, like epigenetic changes or telomere shortening, but if mutations are involved then there may be hopes of slowing genetic damage—or even reversing it.
While just a first step, linking mutation rates to lifespan is a reframing of our understanding of cancer development, and it may open doors to new strategies and therapies for treating cancer or taming the number of health-related concerns that come with aging.
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