American women averaged more than seven children each until the early decades of the 19th century. After 1900, average fertility declined gradually, interrupted only by the baby boom following World War II. Another drop in the total fertility rate (TFR) came in the 1970s, due in large part to delayed marriage, widespread contraceptive use, and changes in abortion laws. The total fertility rate is the average number of children a woman would have in her lifetime based on the childbearing rates of women in a population in a given year. In 2020, the U.S. TFR dropped to 1.64, the lowest level ever recorded.1 Show WHAT CONTRIBUTES TO CHANGING FERTILITY PATTERNS?Historically, fertility in the United States has dropped temporarily during periods of economic decline, such as the Great Depression of the 1930s and the 1970s oil shocks. Such drops have typically lasted two to five years, affecting the timing of fertility but not the overall number of children that a woman would have in her lifetime.2 But in the decade following the 2008 Great Recession, fertility rates continued to fall, with the exception of 2013 to 2014 when they increased slightly. Between 2007 and 2020, the TFR in the United States declined from 2.12 to 1.64.3 This decline may signal a longer-term drop in lifetime fertility shaped by broader social factors, including postponement of marriage and childbearing to older ages and long-term increases in women’s educational attainment and labor force participation.4 Although most American women say they expect to have at least two children, many women delay childbearing whether by choice or circumstance to the point that they may end up having only one child or no children at all.5 Fifteen percent of U.S. women ages 40 to 44 in 2018 were childless.6 In 2011-2015, among American women ages 15 to 44, 20% had two children; 17% had one child; 18% had three or more children, and 45% had not had any children.7 What accounts for these differences? The most predictable and obvious fertility differential is age. For example, in 2011-2015, 83% of women ages 15 to 24 had not had any children, compared with only 15% of women ages 40 to 44. But education, race, religion, and many other social, economic, and cultural factors also influence childbearing. While modern technology has expanded the age span in which women can have children, few women give birth before age 15 or after age 50. Birth rates by the age of the mother follow the same general pattern in most societies regardless of overall fertility levels: Rates are low for women in their teens, peak for women in their 20s or early 30s, and decline thereafter. But comparisons of the age-specific rates in different countries reveal significant variations(see Figure 1). Figure 1: Age-Specific Birth Rates Vary Widely Across Countries, Births per 1,000 Women in Mali, South Korea, and the United States by Age of Mother Sources: Institut National de la Statistique, Cellule de Planification et de Statistique Secteur Santé-Développement Social et Promotion de la Famille, and ICF, Mali Enquête Démographique et de Santé 2018: Rapport de synthèse (2019); CDC, National Center for Health Statistics, National Vital Statistics Reports; and United Nations (UN), Demographic Yearbook 2017 (New York: UN, 2017). Similar trends occur in many of the world’s wealthy countries. In South Korea, the birth rate peaks among women in their early 30s. But in low-income countries with higher fertility rates such as Mali, where the TFR was an estimated 6.3 in 2018, rates typically peak among women in their early 20s and are higher for women of every age.8 During the 1960s and 1970s, postponement of childbearing resulted in a steep drop in the birth rate among American women ages 20 to 24. After 1975, U.S. birth rates rose for women in their 30s, as older mothers had the children they had postponed earlier in life. Today, U.S. birth rates are highest for women in the age groups of 25 to 29 and 30 to 34.9 Figure 2: U.S. Birth Rates Fall for Women in Their 20s, Rise for Women in Their 30s and 40s in Recent Decades, U.S. Birth Rates per 1,000 Women by Age of Mother, 1937–2018Sources: Centers for Disease Control and Prevention, National Center for Health Statistics. The birth rate for women ages 40 to 44 is lower in the United States today than it was during the baby boom years of the 1950s and early 1960s. However, the birth rate for women ages 40 to 44 has risen almost continuously since 1985 due to delays in childbearing at younger ages. The higher birth rates at older ages during the baby boom largely reflected women having third, fourth, or higher-order births rather than first or second births. Teen birth rates remained relatively low in the 1970s and 1980s, despite large increases in the proportion of teenagers who were sexually active. The teen birth rate edged up around 1990. But, by 2020 increases in contraceptive use and a leveling of the share of teens who were sexually active helped reduce the teen birth rate to 15.3—the lowest level ever recorded in the United States. Education and income also play a significant role in fertility. In nearly every contemporary society, people who are more educated and have higher incomes have fewer children than those who are less educated and have lower incomes. In 2017, U.S. women ages 25 and older with an advanced degree had an average of 1.80 children, compared with 2.25 children for women with a high school diploma and 2.70 children for women without a high school diploma.10 FERTILITY RATES ARE FALLING AMONG RACIAL AND ETHNIC MINORITIES AND IMMIGRANTSIn many countries, racial and ethnic minorities have higher fertility rates than the racial/ethnic majority. Often these differences arise from religious beliefs and cultural norms. Immigrants often maintain the childbearing patterns of their homelands when they arrive in a new country. For example, fertility rates for Arabs in Israel and Asians in Russia remain higher than average for the country. But over time, immigrants and their children tend to incorporate the fertility patterns of their adopted country. In the United States, fertility rates have fallen since 1990 among all major racial/ethnic groups, declining fastest among African Americans and Latinas. In 2019, the TFR was 1.61 children per woman for non-Hispanic white women, compared with 1.51 for Asian women, 1.78 for African American women, and 1.94 for Latinas.11
Estimated reading time: 8 minutes Later this month, the U.S. Census Bureau plans to release the first results from the 2020 Census on race and ethnicity. These data will provide a snapshot of the racial and ethnic composition and diversity of the U.S. population as of April 1, 2020. We will release the following measures of diversity to clearly present and analyze the complexity of the 2020 Census results compared to the 2010 Census results: In this blog, we provide a preview of these measures and explain what each can tell you about the nation’s racial and ethnic composition and diversity. The concept of “composition” refers to the racial and ethnic makeup of a population. The concept of “diversity” refers to the representation and relative size of different racial and ethnic groups within a population, where diversity is maximized when all groups are represented in an area and have equal shares of the population.
Categorizing Race and Ethnicity
First, it’s important to know how we collect and tabulate data on race and ethnicity in the 2020 Census. Like other statistical agencies, we follow standards on race and ethnicity set by the U.S. Office of Management and Budget (OMB) in 1997. These standards guide how the federal government collects and presents data on these topics. Per these standards:
For race, the OMB standards identify five minimum categories:
We use a sixth category, Some Other Race, for people who do not identify with any of the OMB race categories. We tabulate statistics on people who report only one race in one of these six “race alone” categories, and we include people who report multiple races in the “Multiracial” population, also referred to as the “Two or More Races” population. For ethnicity, the OMB standards classify individuals in one of two categories: “Hispanic or Latino” or “Not Hispanic or Latino.” We use the term “Hispanic or Latino” interchangeably with the term “Hispanic,” and also refer to this concept as “ethnicity.” The OMB standards also emphasize that people of Hispanic origin may be of any race. In data tables, we often cross-tabulate the race and Hispanic origin categories to display Hispanic as a single category and the non-Hispanic race groups as categories summing up to the total population. These diversity calculations require the use of mutually exclusive racial and ethnic (nonoverlapping) categories. For our analyses, we calculate the Hispanic or Latino population of any race as a category; each of the race alone, non-Hispanic groups as individual categories; and the Multiracial non-Hispanic group as a distinct category. The following groups are used in the diversity calculations:
The recent blog Improvements to the 2020 Census Hispanic Origin and Race Questions and Coding Procedures describes how we code write-in responses into these standard categories.
Diversity Index
One of the measures we will use to present the 2020 Census results is the Diversity Index, or DI. This index shows the probability that two people chosen at random will be from different race and ethnic groups. The DI is bounded between 0 and 1, with a zero-value indicating that everyone in the population has the same racial and ethnic characteristics, while a value close to 1 indicates that everyone in the population has different characteristics. We converted the probabilities into percentages to make the results easier to interpret. In this format, the DI tells us the chance that two people chosen at random will be from different racial and ethnic groups. To illustrate how the DI works, we compare the composition of three hypothetical populations below. In Figure 1, the population is made up of only two large and even groups. The DI for this population indicates that there is a 50% chance that two people chosen at random will be from different race and ethnic groups.
Figure 2, the second hypothetical example, shows a population with four equally sized groups where the DI is 75%. The chance that the two people come from different race and ethnic groups is increased, even though the size of each group is smaller than in the first example.
Figure 3 shows a hypothetical population with four unequally sized groups and a DI of 70%. Comparing Figure 2 and Figure 3, we see that the relative size of the racial and ethnic groups affects the DI score by decreasing the probability when some groups are larger than the others.
The DI for actual data from the 2010 Census for the United States and selected states illustrate how the metric can vary based on the distribution of the population by race and ethnicity. In 2010, there was a 54.9% chance that two people chosen at random from the U.S. population would be from different race or ethnicity groups (Figure 4).
In 2010, the DI varied greatly by state (not shown). Among all states, the DI ranged from a low of 10.8% in Maine to a high of 75.1% in Hawaii.
Prevalence Rankings and Diffusion Score
We can also measure racial and ethnic diversity using prevalence rankings and the diffusion score. With prevalence rankings, which show the most common group in an area, we look at patterns in the percentage of the population that falls into the largest race or ethnic group, second-largest group, and third-largest group. The prevalence ranking approach uses tables or graphs to show the percentages of the largest groups. From the rankings on 2010 Census data, we find:
The diffusion score measures the percentage of the population that is not in the first-, second- or third-largest racial and ethnic groups combined. This metric tells us how diverse and unconcentrated the population is relative to the three largest groups. For example, the diffusion score for the United States was 7.7% in 2010, as 7.7% of the population was not one of the three largest racial or ethnic groups. When we look across the country, we see a lot of variation in the diffusion scores by state in 2010.
Prevalence Mapping
The final conceptual approach to illustrate the racial and ethnic diversity of the population is to map the most prevalent racial or ethnic group for all counties in the United States. These prevalence maps show the geographic distribution of the largest or second-largest racial or ethnic group. It is similar to the prevalence ranking approach shown above. Below we provide examples of prevalence maps for counties using data from the 2010 Census. We will use similar prevalence maps to highlight the racial and ethnic composition and diversity in the 2020 Census results. Figure 5 shows the most prevalent racial or ethnic group for each county in 2010.
For most counties, White alone, non-Hispanic was the most prevalent group. However, we see some regional variation: Figure 6 shows the second-most prevalent racial and ethnic group for each county.
The number of racial or ethnic groups represented in the map increases. For example, the Asian alone, non-Hispanic population and the Multiracial, non-Hispanic population are now represented in some counties on the map as the second-most prevalent group. As with Figure 5, we also see regional patterns in the racial and ethnic distribution of the population.
Measuring Diversity Then and Now
We chose this new set of diversity measures — the DI, prevalence maps, prevalence ranking, and diffusion scores — because they have clear conceptual definitions and interpretations. They also overcome some of the limitations of the diversity measures we have used in the past. In the past, the Census Bureau had sometimes used the concept of “majority” and “minority” for measuring diversity, but this approach has several conceptual and practical challenges that limit its ability to illustrate the complex racial and ethnic diversity of the U.S. population. For example, while some people classify individuals who identify with multiple population groups (such as Hispanic and White; White and Black or African American; and White and Asian) as part of the majority population, others classify them as part of the minority population. The dual identities of these groups highlight the social, political and economic complexities of race and ethnicity in 21st century U.S. society. The inclusion of certain groups as part of the “majority” or “minority” has also become more complex and contested in recent decades, especially as many people may not identify with certain population groups even if that is how they are classified and tabulated per federal standards. The majority-minority approach is ambiguous, and it is further complicated by complex demographic and social realities. To overcome these limitations, we focused on these alternative race and ethnicity diversity measures to illustrate the racial and ethnic composition of the 2020 Census results. We plan to explore other diversity measures as part of our future research with 2020 Census data. The analyses scheduled for release later this month will provide a complementary perspective to the statistics in the 2020 Census Redistricting Data (Public Law 94-171) Summary File and will help the public to understand the racial and ethnic makeup of the U.S. population and the myriad diversity of identities that people share.
Acknowledgment
In 2019, the Census Bureau formed the Disseminating Diversity Working Group to develop a strategy for producing statistics on racial and ethnic diversity in the 2020 Census data products and beyond. The working group comprises subject-matter experts in race and ethnicity, demography and data visualization. The diversity measures included in this blog were developed through research and collaborative discussions among the authors, as well as consultation with external experts and advisors. The blog was written by members of the working group and reflects our efforts to clearly communicate statistics about the racial and ethnic diversity of the U.S. population. |
Place the following racial-ethnic groups in order from the lowest to the highest marriage rates.
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