Population Projections

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1 College of Liberal Arts and Sciences Bureau of Economic and Business Research Florida Population Studies Bulletin 169, June 2014 by Age, Sex, Race, and Hispanic Origin Population Projections for Florida and Its Counties With Estimates for 2013

2 Florida Population Studies Bulletin 169, June 2014 Population Projections by Age, Sex, Race, and Hispanic Origin for Florida and Its Counties, , With Estimates for 2013 Stanley K. Smith Stefan Rayer University of Florida J. Bernard Machen, 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 Stanley K. Smith, Professor Emeritus Scott Cody, Research Demographer 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:

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4 Population Projections by Age, Sex, Race, and Hispanic Origin for Florida and Its Counties, , With Estimates for 2013 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 2013; 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). 3

5 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 doublecounting 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 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 2013 in the following counties: Alachua, Baker, Bradford, Calhoun, Columbia, DeSoto, Dixie, Franklin, Gadsden, Gilchrist, Glades, Gulf, Hamilton, Hardee, Hendry, Holmes, Jackson, Jefferson, Lafayette, Leon, Liberty, Madison, Okeechobee, Santa Rosa, Sumter, Suwannee, Taylor, Union, Wakulla, Walton, and Washington counties. In these counties, we made separate projections for the institutional and noninstitutional 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 2013 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 2013 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 2013 estimates of total population published in Florida Estimates of Population: April 1, 2013, 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 2013 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: LINE23: linear extrapolation of noninstitutional population change for each racial/ ethnic group. LINE13: linear extrapolation of noninstitutional population change for each racial/ ethnic group. 4

6 SHARE23: each racial/ethnic group s share of county non-institutional population change is applied to projected county non-institutional population change. SHARE13: each racial/ethnic group s share of county non-institutional population change is applied to projected county non-institutional population change. EXPO23: exponential extrapolation of non-institutional population change for each racial/ethnic group. SHIFT23: 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 2013 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 65 counties, the final projection was based on CTRL AVE3; in Miami-Dade County, it was based on CTRL AVE7; and in Pinellas County, it was based on an average of SHARE23 and SHIFT23. 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 2013 Florida Population Studies, Bulletin No. 168, 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 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 5

7 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. 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 2013 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 2013 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 2013 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. 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 6

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9 ALACHUA All Races Total 247, , , , , , , , ,068 12,936 13,051 13,448 14,182 14,286 14,544 14, ,217 31,812 32,599 33,659 34,900 35,566 37,239 37, ,295 54,543 54,065 54,092 56,138 56,966 56,702 58, ,958 90,636 91,191 93,274 96, , , , ,171 28,132 29,136 29,673 27,410 26,324 28,071 32, ,169 22,061 24,261 32,522 37,617 41,022 38,394 38, ,458 7,882 8,253 9,008 11,341 14,823 19,193 21,624 Female 127, , , , , , , , ,365 6,323 6,395 6,590 6,949 7,000 7,127 7, ,369 15,775 16,198 16,668 17,266 17,600 18,426 18, ,317 28,756 28,485 28,769 29,880 30,165 30,108 30, ,156 45,252 45,370 46,013 47,588 49,570 52,091 52, ,232 14,871 15,491 15,763 14,215 13,437 13,857 16, ,374 11,830 12,947 17,135 20,232 21,982 20,539 19, ,737 4,921 5,100 5,587 6,713 8,655 11,042 12,752 Non-Hispanic White Total 160, , , , , , , , ,751 6,629 6,610 6,657 6,798 6,710 6,657 6, ,989 17,116 17,322 17,168 17,514 17,413 18,128 17, ,411 33,646 33,142 32,671 33,372 33,373 33,282 33, ,554 58,093 57,771 57,529 58,317 59,552 61,192 60, ,712 21,029 21,443 20,659 18,568 17,301 18,162 20, ,044 17,432 19,193 25,550 28,722 30,323 27,602 26, ,190 6,523 6,806 7,350 9,265 12,240 15,663 17,451 Female 82,050 81,850 82,719 85,263 87,733 89,897 91,797 93, ,255 3,227 3,239 3,262 3,331 3,288 3,262 3, ,288 8,446 8,581 8,492 8,682 8,651 9,002 8, ,582 17,540 17,234 17,226 17,641 17,565 17,583 17, ,318 28,450 28,192 27,747 28,090 28,887 30,030 29, ,692 10,971 11,263 10,834 9,438 8,578 8,644 9, ,023 9,184 10,046 13,196 15,134 15,920 14,414 13, ,892 4,032 4,164 4,506 5,417 7,008 8,862 10,107 Non-Hispanic Black Total 51,115 51,304 52,771 56,979 60,842 64,091 67,025 69, ,242 4,186 4,251 4,408 4,584 4,528 4,659 4, ,033 9,660 9,852 10,374 10,715 10,866 11,283 11, ,505 9,467 9,536 9,844 10,733 11,400 11,468 11, ,951 18,946 19,438 20,778 22,303 23,781 25,071 25, ,561 4,875 5,199 5,843 5,475 5,326 5,816 6, ,902 3,217 3,500 4,611 5,677 6,566 6,526 6, ,121 1,355 1,624 2,202 2,589 Female 27,264 27,303 28,042 30,176 32,141 33,781 35,281 36, ,054 2,037 2,076 2,159 2,252 2,232 2,297 2, ,002 4,807 4,899 5,123 5,301 5,383 5,595 5, ,304 5,246 5,271 5,405 5,840 6,096 6,153 6, ,137 10,074 10,291 10,949 11,654 12,383 13,017 13, ,469 2,654 2,840 3,196 2,985 2,925 3,119 3, ,663 1,844 2,006 2,601 3,257 3,725 3,741 3, ,037 1,359 1,649 Hispanic Total 20,752 21,454 22,328 24,825 27,291 29,556 31,426 33, ,304 1,296 1,308 1,353 1,600 1,731 1,873 2, ,705 3,128 3,381 3,702 3,865 4,129 4,546 4, ,742 7,478 7,566 8,025 8,562 8,884 8,623 8, ,031 7,269 7,553 8,372 9,215 9,940 10,912 11, ,035 1,235 1,385 1,782 1,922 2,153 2,405 2, ,270 1,731 2,229 2,376 2, Female 10,722 11,070 11,512 12,772 14,021 15,167 16,121 16, ,317 1,558 1,692 1,864 1,919 2,043 2,244 2, ,126 3,994 4,058 4,324 4,599 4,778 4,629 4, ,467 3,548 3,663 3,992 4,441 4,793 5,357 5, ,016 1,107 1,212 1, ,014 1,281 1,325 1,

10 BAKER All Races Total 27,115 26,881 27,621 29,589 31,463 33,163 34,637 35, ,933 1,853 1,872 1,927 2,035 2,026 2,116 2, ,114 4,884 4,919 5,061 5,023 5,236 5,365 5, ,482 2,489 2,575 2,644 2,937 2,762 2,758 2, ,477 11,288 11,482 11,978 12,629 13,409 14,150 14, ,153 3,222 3,383 3,780 3,894 3,950 3,999 4, ,349 2,489 2,679 3,405 3,912 4,565 4,663 4, ,033 1,215 1,586 1,720 Female 12,955 12,702 13,029 14,025 14,969 15,826 16,567 17, ,037 1, ,468 2,363 2,385 2,445 2,429 2,541 2,607 2, ,152 1,112 1,131 1,212 1,359 1,249 1,263 1, ,224 5,013 5,070 5,294 5,625 6,019 6,336 6, ,587 1,617 1,700 1,885 1,885 1,928 1,996 2, ,202 1,283 1,383 1,781 2,096 2,396 2,428 2, ,004 Non-Hispanic White Total 22,626 22,295 22,912 24,627 26,264 27,749 29,024 30, ,613 1,551 1,573 1,606 1,692 1,678 1,759 1, ,320 4,116 4,145 4,255 4,208 4,383 4,466 4, ,969 1,969 2,044 2,117 2,363 2,198 2,198 2, ,309 9,055 9,202 9,652 10,243 10,907 11,552 11, ,732 2,757 2,878 3,239 3,364 3,466 3,514 3, ,142 2,260 2,429 3,038 3,460 4,023 4,129 4, ,094 1,406 1,503 Female 11,161 10,941 11,234 12,093 12,918 13,666 14,308 14, ,095 1,993 2,006 2,044 2,027 2,128 2,171 2, ,042 1,152 1,042 1,067 1, ,509 4,337 4,396 4,593 4,923 5,257 5,519 5, ,395 1,399 1,457 1,633 1,639 1,708 1,789 2, ,094 1,164 1,256 1,577 1,829 2,083 2,113 2, Non-Hispanic Black Total 3,747 3,818 3,891 4,034 4,170 4,287 4,399 4, ,857 1,913 1,937 1,948 1,956 2,002 2,068 2, Female 1,448 1,409 1,424 1,501 1,574 1,637 1,690 1, Hispanic Total , Female

11 BAY All Races Total 168, , , , , , , , ,633 10,514 10,603 10,910 11,574 11,817 12,102 12, ,443 26,516 27,003 27,695 28,588 29,107 30,959 31, ,077 15,553 15,445 15,161 16,502 16,901 16,494 17, ,239 69,028 69,341 70,514 72,741 76,695 80,942 81, ,901 22,025 23,134 26,307 24,859 22,534 22,338 25, ,295 19,448 20,531 24,536 28,224 32,410 32,016 31, ,264 6,782 7,235 7,710 9,255 10,564 12,760 14,301 Female 85,196 85,633 87,312 92,004 96, , , , ,182 5,140 5,195 5,346 5,671 5,790 5,929 6, ,042 13,088 13,341 13,624 14,007 14,261 15,189 15, ,825 7,606 7,572 7,525 8,300 8,306 8,151 8, ,821 34,057 34,100 34,664 35,898 38,046 40,350 41, ,717 11,393 12,029 13,497 12,423 11,340 11,174 12, ,819 10,296 10,781 12,740 14,783 16,811 16,470 15, ,790 4,053 4,294 4,608 5,380 6,044 7,219 8,224 Non-Hispanic White Total 136, , , , , , , , ,706 7,574 7,609 7,728 8,041 8,065 8,129 8, ,708 19,483 19,651 19,744 20,117 20,216 21,217 21, ,240 11,686 11,508 11,115 11,779 11,796 11,513 12, ,702 55,272 55,222 55,042 56,251 58,718 61,374 61, ,097 18,884 19,715 22,417 21,055 18,759 18,402 20, ,497 17,454 18,376 21,620 24,543 28,068 27,656 26, ,644 6,104 6,509 6,937 8,322 9,481 11,258 12,596 Female 68,717 68,583 69,608 72,530 75,248 77,713 79,992 81, ,745 3,699 3,728 3,787 3,940 3,952 3,983 3, ,655 9,552 9,638 9,662 9,831 9,888 10,390 10, ,973 5,719 5,644 5,504 5,876 5,806 5,691 5, ,000 27,174 27,066 26,967 27,694 28,968 30,427 30, ,168 9,674 10,167 11,429 10,432 9,361 9,162 10, ,763 9,129 9,522 11,067 12,686 14,394 14,058 13, ,413 3,636 3,843 4,114 4,789 5,344 6,281 7,144 Non-Hispanic Black Total 18,922 19,149 19,634 20,995 22,287 23,513 24,643 25, ,646 1,631 1,649 1,705 1,764 1,795 1,852 1, ,131 4,078 4,110 4,236 4,320 4,422 4,684 4, ,190 2,169 2,198 2,143 2,337 2,366 2,386 2, ,700 7,654 7,755 8,221 8,665 9,241 9,744 9, ,693 1,893 2,061 2,322 2,243 2,215 2,290 2, ,121 1,256 1,367 1,865 2,353 2,776 2,715 2, ,100 Female 9,594 9,712 9,964 10,674 11,365 12,018 12,581 13, ,070 2,052 2,074 2,105 2,116 2,145 2,281 2, ,084 1,069 1,079 1,076 1,204 1,174 1,172 1, ,852 3,817 3,860 4,091 4,320 4,679 4,951 5, ,066 1,198 1,154 1,150 1,171 1, ,055 1,336 1,552 1,504 1, Hispanic Total 8,107 8,948 9,613 11,405 13,184 14,931 16,624 17, ,001 1,018 1,098 1,331 1,464 1,613 1, ,768 2,094 2,347 2,713 3,046 3,255 3,772 3, ,066 1,109 1,140 1,320 1,745 2,088 1,937 2, ,441 3,767 4,029 4,854 5,370 6,188 7,138 7, ,014 1, Female 3,914 4,336 4,669 5,559 6,466 7,358 8,237 8, ,037 1,160 1,336 1,489 1,602 1,853 1, , ,624 1,770 1,888 2,305 2,566 3,032 3,528 3,

12 BRADFORD All Races Total 28,520 27,217 27,507 28,319 29,009 29,589 30,070 30, ,670 1,631 1,624 1,592 1,635 1,585 1,620 1, ,965 3,962 4,003 4,107 4,030 4,057 4,076 4, ,551 2,351 2,350 2,321 2,538 2,507 2,436 2, ,709 11,294 11,191 10,969 11,168 11,362 11,764 11, ,512 3,574 3,691 3,908 3,528 3,245 3,324 3, ,103 3,292 3,455 4,194 4,542 5,083 4,694 4, ,010 1,113 1,193 1,228 1,568 1,750 2,156 2,291 Female 12,510 12,492 12,614 12,984 13,327 13,611 13,857 14, ,943 1,938 1,957 1,994 1,961 1,986 1,998 2, , ,083 1,040 1,031 1, ,754 4,571 4,498 4,347 4,455 4,547 4,721 4, ,702 1,771 1,836 1,971 1,733 1,604 1,645 1, ,656 1,738 1,810 2,163 2,381 2,635 2,457 2, ,022 1,211 1,326 Non-Hispanic White Total 21,325 20,894 21,102 21,696 22,196 22,618 22,965 23, ,217 1,198 1,196 1,178 1,202 1,147 1,180 1, ,002 2,997 3,021 3,071 2,995 3,031 3,017 3, ,732 1,654 1,653 1,664 1,816 1,755 1,727 1, ,820 8,147 8,026 7,725 7,871 7,999 8,285 8, ,907 2,982 3,074 3,291 2,957 2,694 2,755 3, ,758 2,926 3,067 3,675 3,940 4,415 4,088 4, ,065 1,092 1,415 1,577 1,913 2,035 Female 10,125 10,130 10,221 10,489 10,740 10,949 11,134 11, ,479 1,476 1,488 1,504 1,464 1,486 1,481 1, ,854 3,693 3,616 3,446 3,531 3,606 3,740 3, ,420 1,478 1,530 1,684 1,463 1,335 1,375 1, ,458 1,532 1,595 1,859 2,036 2,255 2,117 2, ,055 1,164 Non-Hispanic Black Total 5,908 5,165 5,211 5,338 5,450 5,534 5,606 5, ,210 2,588 2,599 2,630 2,641 2,661 2,733 2, Female 1,955 1,928 1,941 2,009 2,069 2,116 2,148 2, Hispanic Total 1, ,012 1,091 1,158 1,215 1, Female

13 BREVARD All Races Total 543, , , , , , , , ,809 27,026 27,480 28,732 30,295 30,687 32,098 31, ,877 78,132 77,196 79,254 79,834 83,070 85,814 89, ,781 44,121 45,561 42,663 44,663 42,922 44,163 45, , , , , , , , , ,652 82,339 88, ,756 92,876 78,433 74,327 81, ,924 82,484 85, , , , , , ,788 33,185 35,210 35,668 42,119 45,910 56,494 66,243 Female 277, , , , , , , , ,895 13,147 13,465 14,079 14,845 15,037 15,728 15, ,504 38,160 37,758 38,760 39,211 40,927 42,319 44, ,680 20,764 21,689 20,764 21,702 20,671 21,592 22, , , ,497 98, , , , , ,637 42,364 45,380 52,619 48,335 41,077 38,478 41, ,597 44,030 45,547 54,796 63,941 75,830 74,240 70, ,207 19,346 20,353 20,925 24,404 26,704 32,068 37,755 Non-Hispanic White Total 428, , , , , , , , ,752 17,599 17,731 18,120 18,583 18,259 18,794 18, ,613 53,083 51,439 50,676 49,596 50,709 51,761 53, ,448 31,049 31,863 28,410 28,565 26,334 27,082 27, , , , , , , , , ,431 69,341 74,205 83,871 74,419 59,913 55,245 61, ,918 71,555 73,600 89, , , , , ,044 29,991 31,688 31,517 36,780 39,885 48,718 57,251 Female 217, , , , , , , , ,515 8,551 8,688 8,879 9,106 8,947 9,209 8, ,561 25,843 25,043 24,702 24,326 24,963 25,514 26, ,246 14,743 15,271 13,784 13,790 12,686 13,218 13, ,523 77,040 75,078 70,690 71,133 72,786 76,582 76, ,276 35,080 37,417 42,786 38,169 30,818 27,998 30, ,850 37,701 38,771 45,938 53,016 62,394 60,318 55, ,471 17,351 18,168 18,316 21,075 22,849 27,150 32,057 Non-Hispanic Black Total 55,881 58,013 60,153 66,726 72,681 77,768 82,145 85, ,446 4,509 4,605 4,856 5,115 5,253 5,531 5, ,260 12,216 12,263 13,089 13,228 13,824 14,367 15, ,368 6,408 6,585 6,363 7,163 6,850 7,146 7, ,726 21,404 22,121 24,332 26,607 29,068 31,127 32, ,500 6,259 6,850 8,477 8,729 8,677 8,667 9, ,158 5,577 5,927 7,530 9,198 11,177 11,537 11, ,423 1,640 1,802 2,079 2,641 2,919 3,770 4,308 Female 28,778 29,921 31,052 34,490 37,570 40,187 42,322 44, ,143 2,194 2,254 2,370 2,488 2,547 2,682 2, ,990 5,969 6,018 6,373 6,467 6,759 7,045 7, ,806 2,949 3,089 3,156 3,499 3,295 3,486 3, ,996 11,173 11,428 12,322 13,404 14,506 15,376 16, ,009 3,402 3,711 4,569 4,728 4,790 4,756 4, ,917 3,194 3,419 4,384 5,337 6,405 6,589 6, ,040 1,133 1,316 1,647 1,885 2,388 2,758 Hispanic Total 43,943 48,179 51,131 60,049 68,392 75,463 81,510 86, ,851 4,086 4,253 4,702 5,363 5,773 6,296 6, ,610 10,340 10,899 12,490 13,731 14,844 15,850 17, ,606 5,209 5,580 6,352 7,106 7,909 8,027 8, ,613 18,881 19,776 22,592 25,781 27,966 30,590 32, ,747 4,586 5,156 6,772 7,203 7,511 8,089 8, ,453 3,841 4,112 5,535 7,160 9,144 9,672 10, ,063 1,236 1,355 1,606 2,048 2,316 2,986 3,515 Female 22,466 24,649 26,171 30,745 35,024 38,633 41,736 44, ,875 1,997 2,084 2,304 2,628 2,829 3,085 3, ,721 5,070 5,362 6,154 6,736 7,310 7,786 8, ,034 2,400 2,605 3,041 3,486 3,766 3,911 4, ,124 9,700 10,109 11,359 12,877 13,924 15,215 16, ,086 2,529 2,830 3,679 3,959 4,126 4,392 4, ,975 2,203 2,363 3,217 4,074 5,236 5,486 5, ,264 1,442 1,861 2,166 12

14 BROWARD All Races Total 1,748,066 1,784,715 1,802,981 1,855,922 1,902,192 1,947,695 1,990,308 2,029, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,697 84,286 87,353 87, , , , ,736 Female 901, , , , ,066 1,003,802 1,026,889 1,048, ,601 51,216 51,376 52,387 53,192 53,555 54,600 54, , , , , , , , , ,560 76,624 78,967 74,674 78,525 74,688 78,260 76, , , , , , , , , , , , , , , , , , , , , , , , , ,685 53,074 54,668 54,388 61,958 69,939 84,273 95,645 Non-Hispanic White Total 778, , , , , , , , ,341 31,201 30,520 29,335 28,613 27,361 26,794 25, ,737 91,058 88,168 81,262 75,980 73,037 72,172 70, ,742 49,178 50,260 45,263 44,320 38,698 38,223 36, , , , , , , , , , , , , ,874 88,957 73,376 72, , , , , , , , , ,100 64,291 65,248 60,072 67,912 74,278 86,695 92,910 Female 391, , , , , , , , ,724 15,239 14,955 14,374 14,020 13,407 13,129 12, ,041 44,015 42,776 39,640 37,257 35,837 35,457 34, ,128 23,614 23,998 21,875 21,547 18,947 18,778 18, , , , , , , , , ,696 60,463 61,129 60,863 53,908 43,839 36,074 36, ,929 59,988 62,181 71,458 75,934 79,372 73,720 66, ,904 40,188 40,479 36,872 40,100 42,861 48,747 51,775 Non-Hispanic Black Total 463, , , , , , , , ,828 38,141 38,646 39,977 40,554 40,991 42,086 42, , , , , , , , , ,190 54,062 55,543 52,619 55,638 53,696 56,764 56, , , , , , , , , ,344 48,282 52,476 59,024 59,977 58,625 59,773 64, ,839 32,640 35,536 47,370 59,082 69,931 72,616 73, ,110 8,520 9,375 11,277 14,757 18,232 24,842 29,903 Female 247, , , , , , , , ,152 18,732 18,937 19,598 19,891 20,115 20,652 20, ,019 49,788 49,755 50,806 51,340 52,157 53,737 54, ,981 27,329 28,023 26,443 28,205 26,996 28,453 28, , , , , , , , , ,079 26,994 29,358 32,684 33,299 32,756 33,453 35, ,332 18,993 20,584 27,318 34,229 40,117 42,061 42, ,761 5,635 6,160 7,385 9,351 11,673 15,584 19,184 Hispanic Total 438, , , , , , , , ,699 30,473 30,810 32,278 33,700 34,898 36,341 36, ,539 83,839 84,879 88,257 92,087 94,815 98, , ,767 46,733 49,100 48,320 50,739 51,675 54,857 54, , , , , , , , , ,153 45,594 50,284 64,311 70,557 67,863 66,896 66, ,548 33,523 35,974 47,455 60,353 78,933 87,449 93, ,551 10,333 11,458 14,295 17,745 21,685 28,475 35,527 Female 226, , , , , , , , ,553 14,932 15,097 15,816 16,513 17,100 17,807 18, ,760 40,975 41,544 43,415 45,139 46,595 48,511 50, ,760 22,580 23,660 23,010 24,933 24,808 26,880 26, , , , , , , , , ,936 24,778 27,193 34,463 38,157 36,763 36,432 35, ,382 19,596 20,957 27,291 34,142 44,433 49,168 52, ,439 6,544 7,241 9,144 11,201 13,703 17,670 21,888 13

15 CALHOUN All Races Total 14,625 14,621 14,827 15,377 15,891 16,346 16,699 17, ,223 2,167 2,168 2,204 2,178 2,197 2,232 2, ,241 1,252 1,273 1,243 1,301 1,289 1,270 1, ,217 6,089 6,083 6,119 6,240 6,317 6,516 6, ,777 1,873 1,966 2,105 2,045 2,024 2,005 2, ,733 1,789 1,854 2,210 2,425 2,772 2,710 2, ,064 1,144 Female 6,670 6,645 6,733 7,010 7,269 7,504 7,685 7, ,101 1,077 1,081 1,099 1,082 1,082 1,100 1, ,480 2,405 2,396 2,403 2,469 2,525 2,622 2, , , ,171 1,277 1,451 1,410 1, Non-Hispanic White Total 11,569 11,544 11,705 12,154 12,572 12,946 13,224 13, ,794 1,729 1,714 1,733 1,720 1,746 1,759 1, ,629 4,504 4,484 4,526 4,620 4,677 4,806 4, ,497 1,581 1,664 1,753 1,711 1,700 1,682 1, ,550 1,599 1,659 1,978 2,147 2,439 2,379 2, ,026 Female 5,632 5,608 5,684 5,908 6,121 6,314 6,454 6, ,095 2,041 2,040 2,058 2,102 2,145 2,206 2, ,048 1,119 1,262 1,229 1, Non-Hispanic Black Total 2,055 2,053 2,067 2,075 2,087 2,099 2,111 2, ,081 1,070 1,067 1,029 1, ,012 1, Female Hispanic Total ,038 1,093 1, Female

16 CHARLOTTE All Races Total 159, , , , , , , , ,545 5,707 5,804 5,947 6,369 6,455 6,885 6, ,333 16,851 16,512 16,822 16,682 17,593 18,223 19, ,612 9,269 9,700 8,947 9,273 8,708 9,145 9, ,513 46,748 46,920 45,940 48,195 49,271 53,667 54, ,376 28,118 28,665 30,996 30,340 27,050 25,775 27, ,768 41,019 41,946 49,075 50,139 56,613 54,382 55, ,831 15,967 16,757 16,394 19,960 21,272 24,697 25,812 Female 82,216 84,330 85,820 90,192 93,681 96,728 99, , ,692 2,786 2,844 2,914 3,121 3,163 3,374 3, ,428 8,226 8,081 8,260 8,195 8,654 8,971 9, ,014 4,405 4,663 4,325 4,559 4,228 4,481 4, ,540 23,337 23,210 22,457 23,481 23,967 26,378 26, ,916 15,362 15,687 16,474 15,611 13,795 12,818 13, ,259 21,396 22,199 26,597 27,614 30,638 28,836 28, ,367 8,818 9,136 9,165 11,100 12,283 14,395 15,289 Non-Hispanic White Total 139, , , , , , , , ,094 4,123 4,155 4,167 4,400 4,345 4,559 4, ,201 12,511 12,092 12,009 11,674 12,133 12,429 13, ,636 7,039 7,330 6,494 6,602 6,069 6,347 6, ,710 38,215 38,012 36,002 37,138 37,376 40,881 40, ,204 25,564 25,888 27,639 26,758 23,360 21,798 22, ,235 38,289 39,117 45,616 46,068 51,644 49,198 49, ,943 14,942 15,656 15,083 18,443 19,652 22,716 23,599 Female 71,612 72,686 73,639 76,460 78,569 80,373 81,686 82, ,991 2,014 2,036 2,042 2,156 2,129 2,234 2, ,351 6,036 5,844 5,867 5,737 5,966 6,118 6, ,207 3,399 3,538 3,079 3,189 2,958 3,105 3, ,734 19,295 19,067 17,902 18,330 18,339 20,236 20, ,686 13,918 14,118 14,649 13,765 11,944 10,866 11, ,837 19,837 20,569 24,574 25,231 27,786 25,992 25, ,806 8,187 8,467 8,347 10,161 11,251 13,135 13,871 Non-Hispanic Black Total 9,185 9,879 10,282 11,408 12,437 13,369 14,275 15, ,702 1,685 1,662 1,781 1,855 2,010 2,131 2, ,038 1, ,034 1, ,171 3,450 3,616 4,051 4,481 4,834 5,103 5, ,127 1,238 1,469 1,544 1,546 1,660 1, ,326 1,405 1,449 1,736 2,012 2,402 2,442 2, ,040 1,175 Female 4,485 4,844 5,052 5,635 6,138 6,590 7,010 7, ,032 1, ,414 1,475 1,506 1,689 1,930 2,157 2,323 2, ,023 1,180 1,347 1,299 1, Hispanic Total 9,213 10,371 10,912 12,516 13,974 15,297 16,598 17, ,038 1,106 1,220 1, ,030 2,251 2,351 2,579 2,660 2,891 3,071 3, ,080 1,281 1,432 1,446 1,476 1, ,539 3,948 4,132 4,646 5,267 5,728 6,268 6, ,011 1,095 1,404 1,571 1,716 1,857 1, ,021 1,271 1,515 1,892 2,061 2, Female 4,659 5,252 5,530 6,350 7,100 7,778 8,445 9, ,024 1,130 1,177 1,272 1,300 1,425 1,510 1, ,767 1,950 2,028 2,246 2,576 2,821 3,119 3, ,098 1,155 1,

17 CITRUS All Races Total 141, , , , , , , , ,537 5,462 5,563 5,660 6,207 6,358 6,811 6, ,857 15,830 15,599 16,157 16,141 17,103 17,805 19, ,021 8,480 9,010 8,189 8,699 8,355 8,626 8, ,279 41,231 41,646 41,905 45,085 46,588 51,692 52, ,501 23,746 24,535 27,303 27,031 24,939 23,875 24, ,463 33,366 34,169 40,225 41,801 48,595 46,740 48, ,578 12,404 13,276 13,658 16,926 17,878 21,051 22,034 Female 72,877 72,712 74,543 79,702 84,300 88,439 91,676 94, ,754 2,692 2,726 2,773 3,041 3,116 3,338 3, ,219 7,772 7,702 7,972 7,958 8,393 8,744 9, ,804 4,066 4,341 4,024 4,282 4,149 4,241 4, ,855 21,122 21,201 21,148 22,517 23,103 25,652 26, ,806 12,895 13,293 14,478 14,201 13,195 12,373 12, ,922 17,320 18,038 21,794 22,956 26,137 25,116 25, ,517 6,845 7,242 7,513 9,345 10,346 12,212 12,998 Non-Hispanic White Total 127, , , , , , , , ,589 4,497 4,549 4,563 4,956 4,989 5,287 5, ,091 13,149 12,853 13,081 12,918 13,538 14,018 14, ,984 7,262 7,634 6,775 7,072 6,746 6,888 7, ,545 36,464 36,673 36,201 38,618 39,592 44,015 44, ,927 22,016 22,634 25,065 24,502 22,146 20,913 21, ,528 31,393 32,098 37,514 38,732 44,749 42,755 43, ,164 11,918 12,723 13,018 16,031 16,935 19,805 20,696 Female 66,008 65,599 66,989 70,942 74,404 77,469 79,816 81, ,283 2,217 2,229 2,236 2,428 2,445 2,591 2, ,881 6,472 6,362 6,463 6,366 6,638 6,881 7, ,330 3,489 3,685 3,348 3,505 3,361 3,387 3, ,411 18,700 18,700 18,299 19,293 19,638 21,838 22, ,904 11,891 12,183 13,229 12,869 11,738 10,821 11, ,911 16,252 16,891 20,217 21,107 23,885 22,866 23, ,288 6,578 6,939 7,150 8,836 9,764 11,432 12,125 Non-Hispanic Black Total 4,177 4,288 4,504 5,106 5,689 6,250 6,728 7, , ,454 1,431 1,460 1,685 1,858 1,950 2,105 2, ,059 1,369 1,443 1, Female 2,042 2,116 2,241 2,582 2,902 3,212 3,439 3, ,007 1, Hispanic Total 6,584 6,791 7,250 8,519 9,751 10,913 11,933 12, ,379 1,381 1,460 1,682 1,805 2,020 2,197 2, ,018 1, ,279 2,360 2,526 2,939 3,426 3,818 4,248 4, ,037 1,218 1,302 1,433 1, ,178 1,253 1,603 1,624 1, Female 3,316 3,431 3,670 4,328 4,964 5,561 6,068 6, ,076 1, ,133 1,169 1,249 1,444 1,688 1,865 2,118 2, ,

18 CLAY All Races Total 190, , , , , , , , ,869 11,988 12,485 13,591 14,828 15,693 17,006 17, ,301 36,674 36,876 39,435 40,246 43,694 45,798 49, ,222 17,816 19,479 19,745 21,961 20,407 22,042 22, ,157 77,502 79,020 84,973 92, , , , ,024 23,982 25,406 30,209 31,484 30,843 30,323 31, ,377 19,526 21,587 27,894 32,733 39,050 40,393 42, ,915 5,355 5,819 6,828 9,262 11,569 14,815 16,454 Female 97,374 98, , , , , , , ,790 5,864 6,118 6,659 7,266 7,689 8,333 8, ,735 17,959 18,080 19,343 19,826 21,518 22,580 24, ,793 8,594 9,408 9,605 10,646 9,929 10,778 11, ,872 39,960 40,712 43,626 47,281 50,953 54,758 57, ,966 12,460 13,199 15,613 16,363 16,410 16,278 16, ,186 10,296 11,368 14,664 17,252 20,452 21,338 22, ,032 3,228 3,460 4,005 5,308 6,621 8,382 9,428 Non-Hispanic White Total 149, , , , , , , , ,553 8,555 8,816 9,376 10,018 10,374 11,065 11, ,927 26,523 26,392 27,551 27,428 29,402 30,439 32, ,175 12,992 13,933 13,801 15,303 13,828 14,774 15, ,789 59,747 60,194 62,330 66,599 71,736 76,955 80, ,610 20,061 20,969 24,344 24,317 22,907 22,394 23, ,432 17,258 19,000 23,836 27,354 31,848 32,148 32, ,480 4,867 5,272 6,148 8,300 10,305 12,909 14,233 Female 76,060 76,054 78,358 84,804 90,833 96, , , ,178 4,187 4,320 4,594 4,909 5,083 5,422 5, ,667 13,004 12,957 13,527 13,526 14,491 15,019 15, ,857 6,248 6,699 6,714 7,379 6,727 7,188 7, ,508 30,438 30,648 31,654 33,726 35,915 38,332 39, ,063 10,310 10,787 12,422 12,404 12,005 11,802 12, ,054 8,972 9,857 12,336 14,188 16,385 16,631 17, ,733 2,895 3,090 3,557 4,701 5,804 7,204 8,044 Non-Hispanic Black Total 19,177 19,882 21,280 25,216 28,961 32,542 35,695 38, ,527 1,573 1,675 1,893 2,090 2,263 2,536 2, ,976 4,757 4,819 5,328 5,627 6,195 6,605 7, ,981 2,328 2,674 2,721 2,963 2,785 3,168 3, ,193 8,304 8,767 10,508 11,988 13,474 14,838 16, ,522 1,748 1,985 2,632 3,366 3,820 3,748 3, ,123 1,829 2,489 3,415 3,902 4, ,007 Female 9,930 10,293 11,015 13,050 14,990 16,841 18,411 19, ,018 1,097 1,229 1, ,415 2,316 2,351 2,595 2,752 3,012 3,222 3, ,143 1,320 1,333 1,455 1,371 1,561 1, ,404 4,433 4,659 5,539 6,221 6,919 7,492 8, ,053 1,410 1,840 2,118 2,110 2, ,047 1,436 1,938 2,237 2, Hispanic Total 14,609 15,529 16,844 20,551 24,000 27,212 30,136 32, ,388 1,424 1,512 1,729 2,008 2,221 2,470 2, ,916 3,947 4,164 4,795 5,224 5,814 6,315 6, ,527 1,806 2,055 2,337 2,667 2,766 2,931 3, ,006 6,252 6,700 8,158 9,564 10,742 12,064 12, ,208 1,405 1,990 2,388 2,699 2,790 2, ,293 1,798 2,517 2,894 3, Female 7,418 7,889 8,558 10,439 12,212 13,852 15,366 16, ,088 1,210 1, ,922 1,920 2,023 2,338 2,552 2,860 3,100 3, ,115 1,291 1,304 1,430 1, ,112 3,246 3,483 4,206 4,890 5,462 6,057 6, ,047 1,293 1,473 1,556 1, ,383 1,611 1,

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