Population Projections

Transcription

1 College of Liberal Arts and Sciences Bureau of Economic and Business Research Florida Population Studies Bulletin 172, June 2015 Population Projections by Age, Sex, Race, and Hispanic Origin for Florida and Its Counties 2015 With Estimates for

2 Florida Population Studies Bulletin 172, June 2015 Population Projections by Age, Sex, Race, and Hispanic Origin for Stefan Rayer Ying Wang University of Florida W. Kent Fuchs, President College of Liberal Arts and Sciences Dave Richardson, Dean Bureau of Economic and Business Research Christopher McCarty, Director Population Program Stefan Rayer, Program Director Ying Wang, Research Demographer Richard L. Doty, Research Demographer Suzanne Roulston-Doty, Research Demographer Stanley K. Smith, Professor Emeritus Bureau of Economic and Business Research College of Liberal Arts and Sciences University of Florida Ayers Technological Plaza 720 SW 2nd Ave, Suite 150 P. O. Box Gainesville, Florida Phone: Fax:

3 Population Projections by Age, Sex, Race, and Hispanic Origin for Florida and Its Counties, , With Estimates for 2014 The composition of Florida s population has changed substantially in recent decades. Between 1950 and 2010, for example, the proportion of Florida s population younger than age 15 declined from 26.2 to 17.5 percent; the proportion age 65 and older rose from 8.6 to 17.3 percent; and the proportion black declined from 21.7 to 16.9 percent. The Hispanic population increased from 6.0 percent of the total population in 1970 to 22.5 percent in Changes in demographic composition have been even greater for many counties than for the state as a whole. These changes have important implications for planning and public policy. They affect the demand for education, healthcare, housing, recreation, transportation, and many other goods and services. They affect the number and characteristics of persons in the labor force and in public and private retirement systems. They affect the allocation of many types of public funds. Consequently, there is a tremendous need for population projections by age, sex, race, and Hispanic origin. This report provides a summary of our most recent projections by age, sex, race, and Hispanic origin for Florida and each of its counties from ; estimates of those demographic subgroups for 2014; and a description of the methodology used to construct these estimates and projections. Definitions of Race and Ethnicity The decennial census in the United States is based on self-enumeration. Residents of each household are asked to provide the responses they believe best describe their demographic characteristics, based on guidelines established by the U.S. Census Bureau and the U.S. Office of Management and Budget (OMB). These guidelines allow respondents to identify themselves as Hispanic or non-hispanic and as belonging to one or more of several racial groups. It should be noted that Hispanic is an ethnic classification rather than a racial category; that is, people can be identified both by Hispanic origin and by race. The OMB defines Hispanic or Latino as a person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin regardless of race. For data collection and presentation purposes, federal agencies are required to use a minimum of two ethnicities: Hispanic or Latino, and Not Hispanic or Latino. We follow the same guidelines in this report and use the term Hispanic to refer to persons of Hispanic, Latino, or Spanish origin. The three largest racial/ethnic groups in Florida are non-hispanic whites, non-hispanic blacks, and Hispanics. These three groups accounted for 97.0 percent of Florida s population in This report shows population estimates and projections by age and sex for these three racial/ethnic groups. Estimates and projections for the white, nonwhite, and black populations not differentiated by Hispanic origin are available on request. Data Data from the 1990, 2000, and 2010 censuses formed the basis for these estimates and projections. Although census data are generally quite reliable, two issues regarding race and ethnicity complicate their use. First, in 1990 and all previous censuses, respondents were required to identify themselves as belonging to a single race. Starting in 2000, they were permitted to identify themselves as belonging to one or more races. In Florida, 97.5 percent of the population identified themselves as belonging to a single race in 2010 and 2.5 percent identified themselves as belonging to two or more races. These proportions are very similar to those reported in 2000 (97.6 percent and 2.4 percent, respectively). 2

4 Second, although the U.S. Census Bureau defines Hispanic origin as an ethnic classification rather than a racial category, many respondents interpreted it as a racial category and listed their race as Hispanic, Latino, Mexican, Spaniard, or a similar response. In Florida, 3.6 percent of the total population in 2010 classified themselves as belonging to some race other than those listed on the census questionnaire; more than 90 percent of those respondents were of Hispanic origin. In 2000, 4.4 percent of the total population classified themselves as belonging to some race other than those listed on the census questionnaire; again, more than 90 percent of those respondents were of Hispanic origin. Responding to these issues, the National Center for Health Statistics (NCHS) collaborated with the U.S. Census Bureau to create a set of modified 2000 census counts for every state and county in the United States. Using a variety of data sources and techniques, the NCHS assigned people who classified themselves as belonging to more than one race (or who marked some other race on the census questionnaire) to a single primary race. These modifications produced data that were consistent over time, prevented double-counting of people belonging to more than one race, and provided a racial classification for Hispanics who did not identify their race. The NCHS released a comparable set of modified census counts for For 1990, the U.S. Census Bureau made modifications to the 1990 census counts in which persons listing some other race were assigned to a specific race the modified age/race, sex, and Hispanic origin (MARS) files. The estimates and projections described in this report were based on MARS data for 1990 and NCHS data for 2000 and For 2010, we used an updated April 1, 2010 population that includes Count Question Resolution (CQR) changes for Lake, Marion, and Miami-Dade counties from the Vintage 2013 NCHS bridged-race postcensal population estimates. We also made an additional adjustment for Gadsden County to correct for the institutional facility that the 2010 census failed to enumerate in the county. Large institutions (e.g., universities, prisons) account for a significant proportion of the total population in many counties in Florida. In such counties, it is important to account for the impact of these institutions when making population estimates and projections. Consequently, we used institutional records and data from the decennial census to estimate the non-institutional population by age, sex, race, and Hispanic origin for 1990, 2000, 2010, and 2014 in the following counties: Alachua, Baker, Bradford, Calhoun, Columbia, DeSoto, Dixie, Franklin, Gadsden, Gilchrist, Glades, Gulf, Hamilton, Hardee, Hendry, Holmes, Indian River, Jackson, Jefferson, Lafayette, Leon, Liberty, Madison, Okeechobee, Santa Rosa, Sumter, Suwannee, Taylor, Union, Volusia, Wakulla, Walton, and Washington counties. In these counties, we made separate projections for the institutional and non-institutional populations. The final projections for each county were constructed by adding together the institutional and non-institutional populations. The remainder of this report describes the methodology used for making projections of the non-institutional population. METHODOLOGY 2014 Estimates of Total Population by Race and Ethnicity We made estimates of the total number of non- Hispanic whites, non-hispanic nonwhites, and Hispanics for 2014 using a variety of data sources and techniques. Some relied on extrapolations of previous population trends, whereas others incorporated data on births, deaths, and school enrollment by race and ethnicity. Some estimates were based on averages of several of the individual techniques. The final estimate for each racial/ethnic group in each county was based on our judgment regarding which technique was most likely to provide an accurate estimate of the non-institutional population. As a final step, we controlled these estimates of total population by race and ethnicity to the 2014 estimates of total population published in Florida Estimates of Population: April 1, 2014, published by the Bureau of Economic and Business Research in January, A more detailed description of the methodology can be found in an article by Stanley Smith and June Nogle published in the Social Science Quarterly in 2004 (volume 85, pp ). Projections of Total Population by Race and Ethnicity Starting with the 2014 estimates, we made projections of the total non-institutional population of each county for non-hispanic whites, non-hispanic nonwhites, and Hispanics using the following techniques: 3

5 LINE24: linear extrapolation of noninstitutional population change for each racial/ ethnic group. LINE14: linear extrapolation of noninstitutional population change for each racial/ ethnic group. SHARE24: each racial/ethnic group s share of county non-institutional population change is applied to projected county noninstitutional population change. SHARE14: each racial/ethnic group s share of county non-institutional population change is applied to projected county noninstitutional population change. EXPO24: exponential extrapolation of non-institutional population change for each racial/ethnic group. SHIFT24: the change in each racial/ethnic group s share of county non-institutional population is linearly extrapolated and applied to county projections of total non-institutional population. CONST%: each racial/ethnic group s share of the non-institutional population in 2014 is assumed to remain constant over time. AVE7: an average of projections from the seven techniques described above. AVE5: an average of these projections, excluding the highest and lowest. AVE3: an average of these projections, excluding the two highest and the two lowest. CTRL AVE7: AVE7 controlled to medium county projection of total non-institutional population. CTRL AVE5: AVE5 controlled to medium county projection of total non-institutional population. CTRL AVE3: AVE3 controlled to medium county projection of total non-institutional population. The final projection of the total population for each racial/ethnic group in each county was based on our judgment regarding which technique was most likely to provide an accurate forecast of the future non-institutional population. In 63 counties, the final projection was based on CTRL AVE3; in Broward, Gulf and Miami-Dade counties, it was based on CTRL AVE7; and in DeSoto County, it was based on CTRL AVE5. In counties with institutional adjustments, projections of the institutional population were based on institutional records and our judgment regarding future institutional growth. Projections of the racial/ ethnic breakdown of the institutional population were made by applying the racial/ethnic distribution from the 2010 census to the projections of the total institutional population, which were adjusted to reflect changes in the racial/ethnic distribution of the non-institutional population over the projection horizon. Finally, projections of total population by race/ ethnicity were made by adding projections of the institutional population to projections of the noninstitutional population. In all counties, projections for the three racial/ethnic groups were controlled to the medium projections published in Projections of Florida Population by County, , with Estimates for 2014 Florida Population Studies, Bulletin No. 171, Bureau of Economic and Business Research, April Projections by Age, Sex, and Race/Ethnicity Using modified census data and institutional population data for 2000 and 2010, we subtracted the institutional population from the total population for each age, sex, racial, and ethnic group to derive estimates of the non-institutional population in each demographic subgroup. In order to reduce the impact of inconsistencies caused by small data values in many counties, we combined the data for males and females and calculated cohort-survival rates for the non-institutional population by dividing the 2010 estimate for each age, racial, and ethnic group by the 2000 estimate for the corresponding group 10 years younger. These rates were multiplied by weighting factors to account for higher survival rates among females, especially for the older age groups. In many instances, we adjusted the resulting cohort-survival rates to account for apparent data errors and to smooth out differences among age groups. These adjustments were most frequent in counties with 4

6 small populations, especially for the non-hispanic nonwhite and the Hispanic populations. We applied the adjusted cohort-survival rates to the 2010 non-institutional population by age, sex, race, and ethnicity to produce projections for 2020 for the population age 10 and older. For the population less than age 10, we used child-woman ratios based on 2010 NCHS data (i.e., population aged 0 4 divided by females aged 15 44, and population aged 5 9 divided by females aged 20 49). We applied those ratios to the projected female population in 2020 to provide projections of children aged 0 4 and 5 9, respectively. We divided these two age groups into males and females by applying sex ratios derived from the 2010 NCHS data. In some instances, we adjusted the child-woman ratios to account for expected changes in fertility rates. For each of the three racial and ethnic groups, we controlled the non-institutional age and sex projections to the independent projections of the total non-institutional population for 2020 described above. Using these projections as a base, we repeated the process to produce projections for 2030 and We made projections for 2015, 2025, and 2035 for all age groups above age 5 by interpolating between the numbers calculated for the beginning and end of the decade for each age and sex cohort. We made projections for the 0 4 age group by applying child-woman ratios to the relevant female population. These projections were controlled to the independent projections of the non-institutional population described above. As a final step, we added the independent projections of the institutional population, providing projections by age and sex for non-hispanic whites, non-hispanic nonwhites, and Hispanics. Projections at the state level were calculated by adding up the county projections. Projections for other Racial/Ethnic Groups We developed projections for several additional racial/ethnic groups. Using the 2010 NCHS data, we calculated the white/nonwhite proportion of the Hispanic population for each county and applied those proportions to the Hispanic projections to provide a white/nonwhite breakdown of the Hispanic population (in Florida, approximately 76 percent of the Hispanic population identified themselves as white alone in the 2010 census). Adding the Hispanic white population to the non-hispanic white population provided projections of the total white population by age and sex for each county. Using the 2010 NCHS data, we calculated blacks as a proportion of nonwhites for both the Hispanic and non-hispanic populations. We made those calculations separately for each county and based on historical trends and the 2010 values projected those proportions into the future. By applying these proportions to projections of the nonwhite population (for both Hispanics and non-hispanics), we developed projections of the non-hispanic black population and the total black population by age and sex for each county. This report shows projections for non-hispanic whites, non-hispanic blacks, and Hispanics, the three largest racial/ethnic groups in Florida. Projections for these groups do not sum exactly to projections of the total population because they do not include the non-hispanic population that is neither white nor black. Estimates for 2014 The methodology described above was used to make projections by age, sex, race, and Hispanic origin in five-year intervals from 2015 to 2040 for each county in Florida. Estimates for 2014 were made by interpolating between the 2010 modified census counts and the 2015 projections for each age/sex/racial/ ethnic group and controlling those interpolations to the 2014 estimates of total population by race and ethnicity described above. ADDITIONAL DATA This report provides data for abbreviated age groups for non-hispanic whites, non-hispanic blacks, and Hispanics. Data in five-year age groups up to age 85+ (including a breakdown for ages and 18 19) are also available, not only for the three racial/ethnic groups shown here but also for the white, nonwhite, and black populations without reference to Hispanic origin. These data may be ordered online from the Bureau of Economic and Business Research ( Acknowledgement Funding for these projections was provided by the Florida Legislature. 5

7 ALACHUA All Races Total 247, , , , , , , , ,068 12,952 13,006 13,297 13,919 13,980 14,282 14, ,217 32,186 32,580 33,406 34,414 34,974 36,719 36, ,295 54,587 54,375 54,271 56,165 56,924 56,708 58, ,958 90,759 91,023 92,566 95,359 98, , , ,171 28,480 28,968 29,311 26,917 25,811 27,612 31, ,169 23,533 24,753 32,688 37,955 40,491 38,515 37, ,458 8,233 8,471 10,069 12,605 17,388 21,973 25,833 Female 127, , , , , , , , ,365 6,339 6,373 6,516 6,821 6,850 6,998 7, ,369 15,976 16,186 16,549 17,025 17,316 18,167 18, ,317 28,754 28,627 28,841 29,874 30,121 30,090 30, ,156 45,198 45,242 45,542 46,786 48,602 51,155 51, ,232 15,079 15,376 15,507 13,893 13,084 13,550 15, ,374 12,591 13,216 17,200 20,343 21,591 20,474 19, ,737 5,104 5,223 6,189 7,426 10,068 12,580 15,063 Non-Hispanic White Total 160, , , , , , , , ,751 6,546 6,528 6,516 6,593 6,474 6,410 6, ,989 17,087 17,174 16,883 17,092 16,910 17,575 17, ,411 33,478 33,242 32,685 33,277 33,217 33,099 33, ,554 57,532 57,325 56,691 57,107 58,109 59,665 59, ,712 21,033 21,216 20,273 18,093 16,797 17,626 19, ,044 18,539 19,503 25,547 28,838 29,688 27,409 26, ,190 6,779 6,959 8,153 10,217 14,224 17,778 20,609 Female 82,050 82,064 82,513 84,762 86,928 88,959 90,998 92, ,255 3,197 3,199 3,193 3,231 3,172 3,141 3, ,288 8,450 8,509 8,356 8,477 8,409 8,733 8, ,582 17,428 17,282 17,228 17,588 17,481 17,486 17, ,318 28,091 27,930 27,260 27,384 28,041 29,080 28, ,692 11,000 11,131 10,582 9,142 8,246 8,314 9, ,023 9,739 10,216 13,194 15,164 15,537 14,234 13, ,892 4,159 4,246 4,949 5,942 8,073 10,010 11,804 Non-Hispanic Black Total 51,115 52,535 53,343 57,457 61,185 64,549 68,023 71, ,242 4,242 4,276 4,404 4,553 4,492 4,652 4, ,033 9,830 9,934 10,398 10,684 10,825 11,308 11, ,505 9,591 9,629 9,915 10,787 11,456 11,560 12, ,951 19,333 19,600 20,859 22,308 23,821 25,303 25, ,561 5,071 5,239 5,859 5,470 5,327 5,864 7, ,902 3,459 3,625 4,730 5,826 6,646 6,722 6, ,009 1,040 1,292 1,557 1,982 2,614 3,227 Female 27,264 27,916 28,320 30,373 32,229 33,895 35,650 37, ,054 2,068 2,088 2,157 2,237 2,214 2,293 2, ,002 4,888 4,937 5,136 5,280 5,364 5,604 5, ,304 5,299 5,311 5,430 5,857 6,108 6,188 6, ,137 10,253 10,373 10,966 11,607 12,330 13,037 13, ,469 2,756 2,849 3,190 2,969 2,913 3,130 3, ,663 1,979 2,073 2,645 3,305 3,718 3,802 3, ,248 1,596 2,016 Hispanic Total 20,752 22,094 22,566 24,994 27,370 29,624 31,785 33, ,304 1,307 1,315 1,347 1,581 1,708 1,867 2, ,705 3,279 3,411 3,703 3,839 4,091 4,547 4, ,742 7,596 7,645 8,091 8,613 8,925 8,694 9, ,031 7,467 7,618 8,399 9,198 9,919 10,995 11, ,035 1,318 1,396 1,784 1,913 2,142 2,418 2, ,294 1,767 2,230 2,439 2, ,064 Female 10,722 11,392 11,630 12,851 14,049 15,180 16,272 17, ,317 1,637 1,707 1,865 1,906 2,025 2,244 2, ,126 4,064 4,098 4,361 4,625 4,802 4,664 4, ,467 3,628 3,689 3,987 4,407 4,741 5,346 5, ,012 1,101 1,218 1, ,037 1,282 1,363 1,

8 BAKER All Races Total 27,115 26,991 27,377 29,326 31,196 32,979 34,682 36, ,933 1,841 1,846 1,892 1,994 1,987 2,086 2, ,114 4,851 4,857 4,977 4,933 5,143 5,298 5, ,482 2,502 2,545 2,602 2,892 2,723 2,728 2, ,477 11,231 11,346 11,816 12,432 13,226 14,038 14, ,153 3,261 3,340 3,721 3,831 3,891 3,964 4, ,349 2,608 2,714 3,410 3,945 4,529 4,705 4, ,169 1,480 1,863 2,133 Female 12,955 12,753 12,893 13,865 14,794 15,685 16,524 17, ,022 1, ,468 2,350 2,355 2,405 2,384 2,497 2,571 2, ,152 1,109 1,114 1,186 1,334 1,225 1,245 1, ,224 4,977 4,992 5,193 5,497 5,894 6,235 6, ,587 1,637 1,674 1,846 1,842 1,881 1,961 2, ,202 1,345 1,402 1,782 2,110 2,368 2,436 2, ,054 1,233 Non-Hispanic White Total 22,626 22,357 22,642 24,321 25,936 27,480 28,952 30, ,613 1,539 1,545 1,570 1,649 1,636 1,725 1, ,320 4,076 4,080 4,166 4,111 4,280 4,386 4, ,969 1,979 2,013 2,076 2,314 2,156 2,163 2, ,309 8,997 9,059 9,475 10,035 10,703 11,410 11, ,732 2,776 2,833 3,177 3,295 3,400 3,469 3, ,142 2,364 2,457 3,032 3,478 3,974 4,151 4, ,054 1,331 1,648 1,863 Female 11,161 10,963 11,085 11,917 12,719 13,488 14,212 14, ,095 1,973 1,974 2,001 1,979 2,079 2,130 2, ,018 1,125 1,017 1,047 1, ,509 4,299 4,315 4,489 4,793 5,125 5,407 5, ,395 1,406 1,431 1,593 1,594 1,658 1,750 2, ,094 1,220 1,271 1,574 1,837 2,051 2,112 2, ,057 Non-Hispanic Black Total 3,747 3,853 3,928 4,082 4,232 4,376 4,518 4, ,857 1,911 1,951 1,959 1,971 2,024 2,100 2, Female 1,448 1,430 1,444 1,523 1,602 1,679 1,746 1, Hispanic Total , Female

9 BAY All Races Total 168, , , , , , , , ,633 10,468 10,501 10,708 11,279 11,473 11,735 11, ,443 26,563 26,787 27,232 27,916 28,300 30,072 30, ,077 15,382 15,312 14,921 16,155 16,501 16,057 17, ,239 68,616 68,710 69,348 71,123 74,801 78,934 80, ,901 22,365 22,898 25,823 24,266 21,936 21,736 24, ,295 20,190 20,817 24,553 28,193 31,762 31,640 30, ,264 7,197 7,484 8,662 10,417 12,492 14,827 17,141 Female 85,196 86,006 86,839 91,055 95,012 98, , , ,182 5,123 5,145 5,247 5,527 5,622 5,750 5, ,042 13,111 13,228 13,399 13,667 13,866 14,745 14, ,825 7,511 7,482 7,376 8,100 8,077 7,909 8, ,821 33,750 33,728 33,969 34,911 36,869 39,031 39, ,717 11,585 11,887 13,186 12,057 10,942 10,789 12, ,819 10,647 10,934 12,740 14,718 16,402 16,165 15, ,790 4,279 4,435 5,138 6,032 7,103 8,366 9,772 Non-Hispanic White Total 136, , , , , , , , ,706 7,499 7,505 7,553 7,795 7,782 7,826 7, ,708 19,358 19,420 19,323 19,543 19,539 20,467 20, ,240 11,474 11,371 10,891 11,466 11,438 11,128 11, ,702 54,657 54,566 53,936 54,764 56,982 59,507 59, ,097 19,092 19,486 21,962 20,503 18,205 17,841 20, ,497 18,077 18,612 21,600 24,472 27,431 27,254 26, ,644 6,471 6,728 7,780 9,344 11,177 13,053 15,040 Female 68,717 68,603 69,106 71,642 73,963 76,200 78,451 80, ,745 3,668 3,677 3,701 3,820 3,813 3,835 3, ,655 9,488 9,520 9,457 9,544 9,557 10,017 9, ,973 5,609 5,562 5,374 5,705 5,609 5,486 5, ,000 26,792 26,697 26,334 26,825 27,947 29,275 29, ,168 9,803 10,036 11,142 10,095 8,993 8,805 9, ,763 9,413 9,648 11,057 12,618 14,019 13,767 13, ,413 3,830 3,966 4,577 5,356 6,262 7,266 8,459 Non-Hispanic Black Total 18,922 19,334 19,584 20,850 22,060 23,246 24,389 25, ,646 1,629 1,636 1,676 1,724 1,746 1,798 1, ,131 4,071 4,085 4,177 4,233 4,315 4,561 4, ,190 2,172 2,186 2,117 2,298 2,321 2,335 2, ,700 7,666 7,712 8,121 8,521 9,070 9,563 9, ,693 1,966 2,051 2,294 2,205 2,175 2,248 2, ,121 1,330 1,395 1,881 2,371 2,759 2,717 2, ,167 1,376 Female 9,594 9,801 9,927 10,577 11,213 11,832 12,395 12, ,070 2,050 2,060 2,076 2,070 2,093 2,218 2, ,084 1,064 1,068 1,055 1,178 1,143 1,141 1, ,852 3,818 3,835 4,029 4,226 4,560 4,817 4, ,012 1,056 1,178 1,129 1,124 1,144 1, ,056 1,332 1,520 1,484 1, Hispanic Total 8,107 9,453 9,799 11,568 13,305 15,059 16,817 18, ,025 1,035 1,106 1,333 1,465 1,617 1, ,768 2,260 2,392 2,743 3,059 3,260 3,789 4, ,066 1,146 1,161 1,338 1,760 2,104 1,953 2, ,441 3,971 4,106 4,923 5,423 6,250 7,232 7, ,028 1, Female 3,914 4,580 4,751 5,626 6,502 7,390 8,288 9, ,118 1,183 1,352 1,495 1,604 1,861 1, , ,624 1,858 1,918 2,323 2,570 3,029 3,533 3,

10 BRADFORD All Races Total 28,520 27,323 27,632 28,446 29,194 29,882 30,474 30, ,670 1,623 1,621 1,581 1,620 1,574 1,610 1, ,965 3,974 4,003 4,084 4,004 4,033 4,060 4, ,551 2,339 2,352 2,319 2,529 2,501 2,431 2, ,709 11,163 11,207 10,940 11,142 11,349 11,770 11, ,512 3,616 3,685 3,885 3,507 3,231 3,314 3, ,103 3,423 3,526 4,249 4,617 5,093 4,749 4, ,010 1,185 1,238 1,388 1,775 2,101 2,540 2,804 Female 12,510 12,560 12,647 13,021 13,379 13,712 14,003 14, ,943 1,942 1,955 1,982 1,948 1,975 1,989 2, , ,075 1,032 1,024 1, ,754 4,517 4,484 4,312 4,409 4,505 4,677 4, ,702 1,795 1,829 1,949 1,713 1,583 1,627 1, ,656 1,801 1,846 2,190 2,413 2,628 2,470 2, ,028 1,218 1,427 1,608 Non-Hispanic White Total 21,325 20,941 21,134 21,721 22,256 22,742 23,162 23, ,217 1,189 1,188 1,164 1,184 1,129 1,161 1, ,002 2,991 3,007 3,037 2,956 2,990 2,976 2, ,732 1,642 1,649 1,650 1,798 1,736 1,708 1, ,820 8,020 8,001 7,666 7,803 7,930 8,222 8, ,907 3,008 3,061 3,260 2,927 2,668 2,730 3, ,758 3,036 3,125 3,713 3,991 4,404 4,116 4, ,055 1,103 1,231 1,597 1,885 2,249 2,482 Female 10,125 10,155 10,225 10,486 10,744 10,978 11,190 11, ,479 1,472 1,480 1,487 1,444 1,466 1,460 1, ,854 3,627 3,593 3,402 3,476 3,547 3,675 3, ,420 1,493 1,521 1,660 1,438 1,309 1,350 1, ,458 1,585 1,625 1,880 2,059 2,241 2,119 2, ,083 1,241 1,407 Non-Hispanic Black Total 5,908 5,204 5,286 5,423 5,551 5,669 5,771 5, ,210 2,583 2,628 2,657 2,675 2,704 2,787 2, Female 1,955 1,960 1,971 2,043 2,109 2,171 2,214 2, Hispanic Total 1, ,029 1,108 1,185 1,251 1, Female

11 BREVARD All Races Total 543, , , , , , , , ,809 27,046 27,242 28,093 29,352 29,588 30,813 30, ,877 77,176 76,642 77,627 77,541 80,265 82,567 85, ,781 44,565 45,253 41,839 43,509 41,632 42,602 43, , , , , , , , , ,652 84,707 87,692 99,681 90,425 76,119 71,888 78, ,924 84,999 86, , , , , , ,788 35,125 36,404 39,937 47,199 54,177 65,108 78,058 Female 277, , , , , , , , ,895 13,204 13,349 13,765 14,382 14,498 15,098 14, ,504 37,703 37,465 37,963 38,061 39,544 40,695 42, ,680 21,038 21,470 20,289 21,074 19,977 20,761 21, , ,311 99,521 96,024 98, , , , ,637 43,449 44,893 51,315 46,809 39,548 36,952 39, ,597 45,391 46,344 54,742 63,622 73,844 72,675 68, ,207 20,354 21,004 23,233 27,206 31,260 36,853 44,152 Non-Hispanic White Total 428, , , , , , , , ,752 17,487 17,522 17,692 18,023 17,624 18,039 17, ,613 51,814 50,916 49,545 48,203 49,030 49,783 50, ,448 31,192 31,558 27,810 27,830 25,541 26,100 26, , , , , , , , , ,431 71,094 73,422 82,091 72,465 58,145 53,384 58, ,918 73,446 74,757 89, , , , , ,044 31,639 32,721 35,177 41,137 46,888 56,028 67,131 Female 217, , , , , , , , ,515 8,532 8,586 8,669 8,831 8,636 8,839 8, ,561 25,213 24,773 24,151 23,628 24,136 24,525 25, ,246 14,849 15,085 13,444 13,401 12,259 12,705 13, ,523 75,282 74,159 68,958 68,927 70,246 73,447 73, ,276 35,864 36,969 41,672 36,945 29,618 26,817 29, ,850 38,695 39,383 45,882 52,765 60,789 58,996 53, ,471 18,186 18,720 20,262 23,443 26,644 31,150 37,305 Non-Hispanic Black Total 55,881 58,969 60,089 65,927 71,236 76,042 80,292 84, ,446 4,525 4,570 4,742 4,938 5,044 5,294 5, ,260 12,170 12,193 12,819 12,808 13,317 13,792 14, ,368 6,466 6,556 6,240 6,962 6,630 6,884 7, ,726 21,640 21,998 23,867 25,849 28,163 30,113 31, ,500 6,515 6,809 8,312 8,477 8,400 8,377 9, ,158 5,869 6,081 7,561 9,198 10,945 11,414 11, ,423 1,784 1,882 2,386 3,004 3,543 4,418 5,251 Female 28,778 30,397 30,982 34,005 36,710 39,141 41,180 42, ,143 2,208 2,237 2,314 2,402 2,446 2,567 2, ,990 5,954 5,977 6,241 6,255 6,511 6,756 7, ,806 2,991 3,058 3,074 3,383 3,167 3,342 3, ,996 11,233 11,359 12,053 12,959 13,957 14,742 15, ,009 3,521 3,672 4,459 4,570 4,616 4,576 4, ,917 3,364 3,496 4,366 5,279 6,188 6,429 6, ,126 1,183 1,498 1,862 2,256 2,768 3,302 Hispanic Total 43,943 50,014 51,581 59,703 67,185 73,943 79,902 85, ,851 4,179 4,265 4,629 5,198 5,574 6,068 6, ,610 10,663 10,955 12,329 13,354 14,362 15,310 16, ,606 5,420 5,612 6,281 6,940 7,693 7,781 8, ,613 19,415 19,884 22,349 25,176 27,248 29,798 31, ,747 4,892 5,185 6,696 7,033 7,316 7,878 8, ,453 4,096 4,259 5,579 7,168 8,962 9,600 10, ,063 1,349 1,421 1,840 2,316 2,788 3,467 4,255 Female 22,466 25,582 26,387 30,538 34,351 37,774 40,803 43, ,875 2,045 2,090 2,268 2,547 2,731 2,973 3, ,721 5,238 5,390 6,073 6,551 7,072 7,521 8, ,034 2,506 2,609 3,008 3,393 3,664 3,778 3, ,124 9,933 10,145 11,179 12,486 13,426 14,647 15, ,086 2,691 2,846 3,637 3,865 4,019 4,277 4, ,975 2,353 2,449 3,243 4,082 5,133 5,447 5, ,130 1,427 1,729 2,160 2,619 10

12 BROWARD All Races Total 1,748,066 1,803,903 1,818,678 1,891,345 1,953,078 2,008,957 2,059,286 2,105, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,697 85,781 87,305 92, , , , ,891 Female 901, , , ,267 1,003,688 1,031,767 1,057,937 1,081, ,601 51,495 51,750 53,202 54,285 54,697 55,689 55, , , , , , , , , ,560 77,993 79,401 75,797 80,292 76,566 80,039 78, , , , , , , , , , , , , , , , , , , , , , , , , ,685 53,737 54,502 57,156 65,682 78,403 93, ,040 Non-Hispanic White Total 778, , , , , , , , ,341 30,560 30,106 28,661 27,749 26,510 26,065 25, ,737 88,868 87,124 79,500 73,843 70,888 70,338 69, ,742 49,290 49,663 44,340 43,167 37,680 37,330 36, , , , , , , , , , , , , ,011 86,702 71,886 71, , , , , , , , , ,100 63,781 63,933 60,048 67,469 77,138 88,801 98,192 Female 391, , , , , , , , ,724 14,950 14,752 14,044 13,597 12,990 12,772 12, ,041 43,014 42,243 38,780 36,186 34,783 34,535 34, ,128 23,551 23,651 21,347 20,932 18,379 18,292 17, , , , , , , , , ,696 60,223 60,336 59,317 52,186 42,295 35,024 35, ,929 61,762 62,952 71,411 75,725 77,735 72,993 65, ,904 39,587 39,496 36,299 39,254 43,627 49,141 53,586 Non-Hispanic Black Total 463, , , , , , , , ,828 38,496 38,955 40,739 41,507 41,780 42,528 42, , , , , , , , , ,190 55,049 56,107 53,847 57,300 55,157 57,752 57, , , , , , , , , ,344 50,553 52,931 60,361 61,720 60,249 61,055 65, ,839 35,046 36,893 49,542 62,507 72,717 75,954 75, ,110 9,317 9,875 13,469 17,759 23,417 30,845 38,193 Female 247, , , , , , , , ,152 18,884 19,088 19,972 20,358 20,502 20,869 20, ,019 49,939 50,202 51,903 52,644 53,333 54,422 55, ,981 27,688 28,169 26,868 28,902 27,533 28,796 28, , , , , , , , , ,079 28,176 29,490 33,282 34,123 33,516 34,026 36, ,332 20,302 21,318 28,331 35,810 41,147 43,392 42, ,761 6,140 6,489 8,754 11,197 14,803 19,149 24,058 Hispanic Total 438, , , , , , , , ,699 31,232 31,639 33,751 35,706 37,173 38,785 39, ,539 86,177 87,404 92,586 97, , , , ,767 48,995 50,590 50,784 54,197 55,492 58,916 59, , , , , , , , , ,153 48,932 51,665 67,592 75,271 72,970 72,178 71, ,548 36,254 37,959 50,796 65,868 85,449 95, , ,551 11,428 12,156 17,158 21,652 28,270 36,402 46,891 Female 226, , , , , , , , ,553 15,304 15,503 16,538 17,496 18,215 19,005 19, ,760 42,147 42,777 45,544 48,020 49,757 51,903 53, ,760 23,559 24,277 24,184 26,525 26,639 28,752 28, , , , , , , , , ,936 26,530 27,949 36,221 40,713 39,530 39,310 38, ,382 21,174 22,139 29,223 37,306 48,114 53,966 57, ,439 7,233 7,687 10,932 13,665 17,814 22,633 28,888 11

13 CALHOUN All Races Total 14,625 14,592 14,589 15,055 15,500 15,919 16,288 16, ,223 2,137 2,132 2,142 2,099 2,111 2,142 2, ,241 1,247 1,248 1,205 1,259 1,244 1,220 1, ,217 6,019 5,932 5,924 6,012 6,072 6,264 6, ,777 1,894 1,928 2,046 1,977 1,949 1,932 1, ,733 1,831 1,868 2,196 2,401 2,695 2,657 2, ,208 1,344 Female 6,670 6,616 6,653 6,874 7,094 7,304 7,491 7, ,101 1,064 1,064 1,067 1,042 1,039 1,055 1, ,480 2,363 2,352 2,330 2,375 2,421 2,512 2, ,163 1,262 1,405 1,374 1, Non-Hispanic White Total 11,569 11,513 11,549 11,926 12,288 12,629 12,925 13, ,794 1,697 1,685 1,683 1,658 1,677 1,688 1, ,629 4,435 4,392 4,392 4,458 4,501 4,626 4, ,497 1,600 1,632 1,705 1,654 1,637 1,620 1, ,550 1,637 1,672 1,965 2,125 2,369 2,331 2, ,086 1,202 Female 5,632 5,585 5,615 5,796 5,975 6,144 6,293 6, ,095 2,008 2,001 1,996 2,021 2,054 2,111 2, ,041 1,106 1,222 1,197 1, Non-Hispanic Black Total 2,055 2,051 2,013 2,018 2,030 2,038 2,046 2, ,081 1,065 1, Female Hispanic Total ,057 1, Female

14 CHARLOTTE All Races Total 159, , , , , , , , ,545 5,681 5,728 5,818 6,213 6,269 6,623 6, ,333 16,493 16,320 16,486 16,313 17,108 17,561 18, ,612 9,377 9,593 8,777 9,086 8,496 8,834 8, ,513 46,201 46,254 44,975 47,093 47,993 51,823 52, ,376 27,945 28,176 30,239 29,503 26,223 24,792 26, ,768 41,868 42,534 48,886 50,227 55,208 53,341 53, ,831 16,902 17,478 19,043 23,068 26,224 29,604 32,102 Female 82,216 84,751 85,636 90,110 93,791 96,817 98, , ,692 2,779 2,807 2,851 3,044 3,072 3,245 3, ,428 8,059 7,983 8,097 8,009 8,414 8,639 9, ,014 4,472 4,597 4,229 4,454 4,111 4,316 4, ,540 22,924 22,833 21,901 22,809 23,186 25,253 25, ,916 15,262 15,397 16,001 15,095 13,255 12,228 12, ,259 21,994 22,502 26,480 27,606 29,781 28,122 27, ,367 9,261 9,517 10,551 12,774 14,998 17,153 18,834 Non-Hispanic White Total 139, , , , , , , , ,094 4,071 4,080 4,043 4,245 4,165 4,329 4, ,201 12,121 11,894 11,669 11,288 11,650 11,829 12, ,636 7,081 7,220 6,320 6,399 5,845 6,055 6, ,710 37,502 37,340 35,023 35,972 36,034 39,083 38, ,204 25,290 25,403 26,880 25,905 22,516 20,830 21, ,235 39,029 39,621 45,347 46,037 50,179 48,085 47, ,943 15,807 16,331 17,553 21,323 24,254 27,260 29,415 Female 71,612 72,822 73,391 76,250 78,480 80,262 81,314 82, ,991 1,992 1,999 1,981 2,080 2,041 2,121 2, ,351 5,850 5,745 5,701 5,544 5,728 5,819 6, ,207 3,412 3,476 2,985 3,083 2,840 2,955 2, ,734 18,843 18,689 17,354 17,658 17,578 19,194 19, ,686 13,765 13,835 14,180 13,245 11,400 10,288 10, ,837 20,368 20,827 24,421 25,171 26,918 25,262 24, ,806 8,592 8,820 9,628 11,699 13,757 15,675 17,134 Non-Hispanic Black Total 9,185 10,077 10,308 11,475 12,552 13,493 14,314 15, ,702 1,665 1,655 1,765 1,841 1,986 2,086 2, ,050 1, ,016 1, ,171 3,510 3,600 4,028 4,462 4,808 5,034 5, ,173 1,231 1,459 1,538 1,538 1,639 1, ,326 1,458 1,491 1,769 2,060 2,419 2,465 2, ,041 1,230 1,424 Female 4,485 4,943 5,062 5,661 6,182 6,632 7,003 7, ,009 1, ,414 1,479 1,499 1,673 1,911 2,130 2,270 2, ,034 1,196 1,338 1,291 1, Hispanic Total 9,213 10,695 11,025 12,721 14,288 15,636 16,818 17, ,047 1,115 1,216 1, ,030 2,305 2,366 2,600 2,694 2,919 3,068 3, ,041 1,089 1,294 1,455 1,467 1,481 1, ,539 4,049 4,162 4,697 5,355 5,823 6,314 6, ,055 1,101 1,419 1,597 1,745 1,871 1, ,025 1,053 1,310 1,572 1,934 2,104 2, Female 4,659 5,416 5,584 6,448 7,247 7,929 8,530 9, ,024 1,156 1,184 1,283 1,317 1,438 1,508 1, ,767 1,991 2,040 2,259 2,602 2,838 3,105 3, ,123 1,180 1,

15 CITRUS All Races Total 141, , , , , , , , ,537 5,413 5,453 5,477 5,950 6,062 6,465 6, ,857 15,463 15,322 15,655 15,513 16,336 16,937 18, ,021 8,602 8,856 7,943 8,383 8,007 8,226 8, ,279 40,713 40,835 40,645 43,389 44,676 49,406 50, ,501 23,691 24,036 26,467 25,988 23,890 22,796 23, ,463 33,911 34,442 39,839 41,278 46,927 45,386 46, ,578 13,005 13,521 14,897 18,370 20,362 23,473 25,226 Female 72,877 72,851 73,763 78,397 82,502 86,307 89,296 91, ,754 2,661 2,672 2,684 2,916 2,970 3,168 3, ,219 7,609 7,561 7,725 7,644 8,017 8,315 8, ,804 4,125 4,255 3,890 4,115 3,963 4,032 4, ,855 20,759 20,746 20,436 21,556 22,021 24,309 24, ,806 12,835 13,004 13,971 13,576 12,530 11,719 12, ,922 17,743 18,168 21,576 22,625 25,154 24,237 24, ,517 7,119 7,357 8,115 10,070 11,652 13,516 14,714 Non-Hispanic White Total 127, , , , , , , , ,589 4,441 4,457 4,412 4,746 4,751 5,008 4, ,091 12,791 12,619 12,663 12,398 12,913 13,310 14, ,984 7,328 7,503 6,567 6,806 6,455 6,555 6, ,545 35,926 35,948 35,083 37,125 37,914 41,988 42, ,927 21,909 22,168 24,287 23,540 21,195 19,940 20, ,528 31,877 32,347 37,140 38,234 43,180 41,480 41, ,164 12,476 12,953 14,184 17,380 19,258 22,064 23,663 Female 66,008 65,615 66,303 69,810 72,848 75,649 77,785 79, ,283 2,183 2,184 2,162 2,326 2,328 2,454 2, ,881 6,310 6,243 6,257 6,106 6,332 6,530 6, ,330 3,522 3,612 3,234 3,365 3,205 3,215 3, ,411 18,341 18,292 17,672 18,448 18,699 20,668 20, ,904 11,800 11,916 12,758 12,290 11,129 10,227 10, ,911 16,631 17,011 20,014 20,803 22,976 22,048 22, ,288 6,828 7,045 7,713 9,510 10,980 12,643 13,709 Non-Hispanic Black Total 4,177 4,341 4,451 5,017 5,573 6,105 6,570 7, , ,454 1,419 1,433 1,639 1,801 1,880 2,027 2, ,051 1,335 1,418 1, Female 2,042 2,148 2,210 2,529 2,832 3,123 3,339 3, , Hispanic Total 6,584 6,930 7,167 8,361 9,531 10,632 11,615 12, ,379 1,399 1,437 1,637 1,746 1,943 2,108 2, , ,279 2,402 2,485 2,865 3,326 3,698 4,111 4, ,012 1,181 1,259 1,387 1, ,169 1,244 1,562 1,589 1, Female 3,316 3,505 3,627 4,244 4,844 5,406 5,890 6, ,033 1, ,133 1,188 1,226 1,400 1,628 1,788 2,025 2, ,

16 CLAY All Races Total 190, , , , , , , , ,869 12,249 12,516 13,611 14,907 15,860 17,271 17, ,301 36,857 37,024 39,541 40,546 44,219 46,565 50, ,222 18,684 19,555 19,823 22,154 20,721 22,449 23, ,157 78,281 79,163 85,139 93, , , , ,024 24,630 25,380 30,156 31,600 31,184 30,802 32, ,377 20,930 22,112 28,337 33,673 39,616 41,695 43, ,915 5,772 6,067 7,980 10,758 14,480 18,047 21,146 Female 97, , , , , , , , ,790 5,997 6,133 6,670 7,304 7,771 8,463 8, ,735 18,051 18,140 19,394 19,958 21,777 22,943 24, ,793 8,996 9,415 9,605 10,707 10,040 10,946 11, ,872 40,305 40,735 43,579 47,400 51,336 55,375 58, ,966 12,782 13,166 15,522 16,350 16,475 16,439 16, ,186 11,032 11,649 14,892 17,710 20,673 21,902 22, ,032 3,451 3,604 4,643 6,147 8,232 10,188 12,019 Non-Hispanic White Total 149, , , , , , , , ,553 8,601 8,732 9,253 9,888 10,259 10,959 11, ,927 26,241 26,183 27,224 27,130 29,130 30,204 32, ,175 13,353 13,830 13,654 15,166 13,741 14,686 15, ,789 59,478 59,717 61,659 66,015 71,350 76,746 80, ,610 20,344 20,809 24,080 24,097 22,774 22,317 23, ,432 18,387 19,379 24,052 27,913 31,914 32,730 32, ,480 5,223 5,481 7,153 9,589 12,810 15,634 18,132 Female 76,060 76,815 78,064 84,506 90,852 96, , , ,178 4,212 4,279 4,534 4,845 5,027 5,370 5, ,667 12,869 12,847 13,367 13,371 14,357 14,895 15, ,857 6,408 6,633 6,618 7,294 6,659 7,127 7, ,508 30,249 30,352 31,210 33,262 35,515 37,937 39, ,063 10,449 10,690 12,227 12,218 11,821 11,664 12, ,054 9,550 10,056 12,448 14,451 16,363 16,827 17, ,733 3,078 3,207 4,102 5,411 7,162 8,702 10,160 Non-Hispanic Black Total 19,177 21,002 21,815 25,981 30,169 34,279 37,986 41, ,527 1,653 1,711 1,935 2,155 2,353 2,658 2, ,976 4,880 4,932 5,465 5,820 6,460 6,947 7, ,981 2,549 2,737 2,794 3,074 2,917 3,341 3, ,193 8,701 8,972 10,792 12,445 14,134 15,728 17, ,522 1,898 2,028 2,702 3,489 4,005 3,965 3, ,084 1,180 1,917 2,649 3,619 4,204 4, ,143 1,388 Female 9,930 10,859 11,278 13,413 15,560 17,662 19,489 21, ,050 1,140 1,288 1, ,415 2,376 2,403 2,662 2,842 3,141 3,385 3, ,250 1,344 1,358 1,502 1,426 1,638 1, ,404 4,632 4,767 5,673 6,426 7,207 7,869 8, ,006 1,071 1,441 1,899 2,211 2,222 2, ,088 1,513 2,027 2,380 2, Hispanic Total 14,609 16,905 17,687 21,717 25,680 29,472 33,003 36, ,388 1,528 1,582 1,816 2,129 2,380 2,673 2, ,916 4,233 4,370 5,048 5,561 6,246 6,851 7, ,527 2,014 2,154 2,465 2,846 2,986 3,189 3, ,006 6,759 7,029 8,604 10,219 11,618 13,198 14, ,362 1,472 2,099 2,550 2,918 3,049 3, ,388 1,952 2,740 3,198 3, ,108 Female 7,418 8,582 8,978 11,015 13,032 14,954 16,761 18, ,043 1,166 1,310 1, ,922 2,058 2,123 2,461 2,716 3,073 3,363 3, ,023 1,177 1,372 1,407 1,551 1, ,112 3,506 3,648 4,413 5,187 5,845 6,548 7, ,104 1,381 1,593 1,700 1, ,056 1,506 1,781 2,