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How Many People in the United States Are Experiencing Homelessness?

The economic effects of the coronavirus pandemic in the United States include an unemployment rate higher than at any time in the country’s history—including the Great Depression. As an unprecedented number of Americans struggle with job loss, many of them may lose their homes. Many others may lose their homes due to natural disasters or other crises. As these events fluctuate, so too may the number of people without a home. So how do we know how many people are experiencing homelessness in the United States?

We don’t. We have only widely differing estimates based on varying methodologies and definitions.

Estimates of homelessness in the United States range from fewer than 600,000 to more than 1.5 million people, and the estimates vary by source. The two key sources of data—the U.S. Department of Housing and Urban Development Point-in-Time Count, and the National Center for Education Statistics Count of Students Experiencing Homelessness—vary greatly in their coverage and in their annual estimates.

The HUD Point-in-Time Count—One Night Only

The U.S. Department of Housing and Urban Development (HUD) captures data on people experiencing homelessness through point-in-time (PIT) counts. PIT counts take place nationwide and are conducted on one night in the last week of January each year. HUD mandates that programs that receive funding to assist people experiencing homelessness, called Continuum of Care Programs (CoC), organize a count in their jurisdiction. The count itself is conducted by project staff and community volunteers. The CoC can choose to conduct their count either through a complete count or a sample. The sample method must follow HUD standards for counting and estimating the population.

The PIT counts both sheltered and unsheltered people experiencing homelessness. People included in the sheltered count sleep in shelters, transitional housing, or hotels and motels paid for by charities or government programs. Those who sleep in cars, parks, encampments, and other places not designated for regular sleeping are included in the unsheltered count.

HUD does not consider people who are temporarily doubled up with family or friends as homeless. This standard misses many people who lack permanent housing. In particular, parents with children may be less likely to seek group shelters and interact with authorities for fear of losing custody of their children.1

HUD provides a one-night snapshot of an experience that is often fluid for people who experience homelessness. The count does not include people who fall in and out of homelessness throughout the year. Additionally, changes in the count from year to year may reflect either an actual change or a change in the count’s accuracy. HUD itself cautions against drawing conclusions or trends from the count since data quality review is limited, reliability and consistency differ between CoCs, and methods may change between reporting periods.

Given these limitations, it is likely that the PIT undercounts the number of people experiencing homelesseness. These estimates can best be thought of as a snapshot of the minimum number of people who are homeless in a community, a state, or the nation.

The 2019 PIT count identified about 568,000 people experiencing homelessness. The states with the largest populations of people experiencing homelessness were California (151,000), New York (92,000), and Florida (28,000).

The NCES Count of Students Experiencing Homelessness—School Children Only

Another source of data on the number of people experiencing homelessness is the National Center for Education Statistics (NCES). Housed within the U.S. Department of Education, NCES compiles data on public school students experiencing homelessness during the school year. The count uses local school enrollment data that are submitted to the states and then reported to the Department of Education.

Unlike the one-night PIT count, the NCES count covers the entire school year and more accurately captures the fluid nature of homelessness. NCES defines students experiencing homelessness more broadly than the PIT count to include youth who are doubled up in housing and other temporary circumstances. However, this count includes only public school students and does not track adults experiencing homelessness. This count also does not include children who have dropped out of school, children in private schools, young children who are not yet enrolled in school, and children who experience homelessness outside of the school year.

According to NCES, more than 1.5 million students experienced homelessness during the 2017-2018 school year. This estimate is more than double the PIT count for 2018.More than 390,000 of these students were living at a shelter, staying at a hotel or motel, or were unsheltered. The remainder were doubled-up. California (263,000), Texas (231,000), and New York (153,000) had the largest populations of students experiencing homelessness during the 2017-2018 school year.

Which Estimate Is Best?

Both the PIT and NCES counts have advantages and challenges. Table 1 provides a comparison of the two estimates.

Table 1. Comparison of Data Sources on Homelessness in the United States

wdt_ID Data Source Type Universe Excludes Time Period
1 HUD Point-in-Time Count Enumeration (at selected locations) Entire population in selected communities Anyone doubled-up; communities not on HUD’s list One night (last week of January)
2 NCES Education for Homeless Children and Youth Administrative records Public school students Anyone not enrolled in public school School year

Note: The HUD Point-in-Time counts occur only in some communities and likely underestimate the population experiencing homelessness.

The PIT and NCES estimates both have well-documented undercount issues. NCES does not count adults or children not enrolled in school. PIT does not count anyone who is doubled-up. Data users should be aware of these limitations when working with either data source.

Crowds in a stadium with cots.

Disasters Raise Risk of a Homeless Undercount in 2020 Census

Counting people experiencing homelessness is not an easy task during any census, and the coronavirus pandemic, wildfires, and hurricanes have made the process even more complicated in 2020.

Despite rigorous efforts by the Census Bureau to count everyone in the United States, many people experiencing homelessness are likely to be missed in the 2020 Census count. The Census Bureau had already identified people experiencing homelessness as a hard-to-count population because they have more difficulty accessing the typical modes of responding to the survey—by internet, phone, or mail—than people with a permanent address.1 Then the pandemic’s effects on everyday life delayed census field operations. The rescheduled dates to count people experiencing homelessness—Sept. 22-24, 2020—place count efforts in the middle of peak wildfire and hurricane seasons. This confluence of crises magnifies the challenge of conducting a complete and accurate count of an often-overlooked population.

Counting People Where They Sleep

The goal of the 2020 Census is to count everyone once, only once, and at their “usual residence.” Usual residence is defined as the location where a person lives and sleeps most of the time. If people do not have a permanent home, they should be counted at the location where they are on Census Day, April 1, 2020. For people experiencing homelessness, their location on Census Day may be unsheltered (including living in a vehicle), at a shelter or transitional housing, at a hotel or motel, or doubled up in another household.

People who are doubled-up on Census Day should be counted in the household where they are staying on that day, and the census questionnaire includes prompts to help ensure everyone is counted. But the Census Bureau has identified the doubled-up population as hard-to-count because, despite prompts in the questionnaire, they may still be missed.

For people staying at shelters and those who are unsheltered, the Census Bureau aims to count people at the locations where they receive services, like soup kitchens, shelters, and mobile food vans, and at targeted outdoor locations like parks, under bridges, at bus depots, and other areas. To identify such count locations, the Census Bureau uses a combination of internet research and outreach to local elected officials and advocacy organizations.

Due to the coronavirus pandemic, however, both service-based and outdoor count operations were delayed. Service-based enumeration, originally scheduled for March 30 to April 1, has been delayed to September 22-24. The outdoor count, originally scheduled for April 1, will now take place from September 23-24. Because of these delays, people will no longer be counted where they were on April 1 but rather where they are staying in September. This shift—and the reasons for it—raise questions: Are the same service locations open? Are the same people using those services? Are people avoiding services to reduce their risk of exposure to the coronavirus that causes COVID-19, making them even harder to enumerate? All of these issues complicate the count of people experiencing homelessness in 2020.

Counting During Crises Heightens the Risk of Undercount

The shift in operations has also moved the count into peak hurricane and wildfire seasons. Just as census enumerators are preparing to count people outdoors and at service-based locations, serious natural disasters are ravaging parts of the nation. Wildfires have led to hazardous air quality across much of the West Coast, forcing many people to stay indoors. Hurricane Sally, which hit the Gulf Coast on Sept. 16, 2020, has severely damaged infrastructure across several states. People who would normally be outdoors may not be in their “usual” locations, and services may be dramatically disrupted in areas that have been affected by disasters.

The closure of libraries and other community facilities further compounds the challenge of counting. If people experiencing homelessness are missed in service-based and unsheltered enumeration, they can still self-respond to the census through September 30. Public facilities such as libraries, schools, and community centers were expected to serve as outreach locations for 2020 Census self-response. At libraries, for example, people without access to the internet or a computer could learn about the census and use a computer to respond online. However, due to the coronavirus pandemic, many of these facilities are closed. Even if a facility is open, people may avoid public places to lower their risk of contracting the coronavirus.

Communities Could Lose Crucial Funding For Services

Official estimates of homelessness in the United States range from 568,000 to more than 1.5 million people (and both are underestimates). Given those staggering numbers, the Census Bureau faces a major challenge in enumerating this large, hard-to-count population. And because of ongoing natural disasters and the economic effects of the coronavirus pandemic, it’s likely that the number of people experiencing homelessness has increased in 2020.

The 2020 Census will be used to reapportion congressional seats, redraw voting districts, and allocate more than $1 trillion in federal funds each year—including funds that assist people experiencing homelessness. Data from the 2020 Census will be used by governments and nonproft organizations to determine needs for roads, hospitals, and other public services. An undercount of people without a permananent address would reduce funds for programs that serve the United States’ most vulnerable residents. Such an undercount will be magnified in local areas with large numbers of people experiencing homelessness and in areas where the count will be most disrupted. Communities hit the hardest by the pandemic and natural disasters could lose crucial funding.

As one of several vital nationwide operations destabilized by the coronavirus pandemic, wildfires, and hurricanes, the 2020 Census faces more challenges than usual in counting people experiencing homelessness. But a complete and accurate count is vital to supporting these populations and the communities that serve them.

References

1U.S. Census Bureau, “Counting the Hard to Count in a Census,” Select Topics in International Censuses, July 2019, https://www.census.gov/content/dam/Census/library/working-papers/2019/demo/Hard-to-Count-Populations-Brief.pdf

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Life on Hold: How the Coronavirus Is Affecting Young People’s Major Life Decisions

The past two decades have been tumultuous for the United States. During the first 20 years of the 21st century, the nation experienced a major terrorist attack, a housing market meltdown, a severe economic recession, a significant downturn in the stock market, and a pandemic that led to the highest unemployment rate since the Great Depression.

The coronavirus and the disease it causes, COVID-19, are affecting all Americans. Older people are most at risk of severe health issues related to the virus, but young adults—ages 25 to 34—may be most vulnerable to its long-term social and economic impacts. Those in their early 30s reached young adulthood during the Great Recession of 2007 to 2009 and experienced one of the most challenging job markets in U.S. history. Now those in their mid-20s are entering prime marriage and family formation years just as the coronavirus pandemic is causing extensive economic and social disruptions.

Even before the crisis hit, more young Americans had been postponing key life events that often mark the transition to adulthood. Fewer young adults in their 20s and 30s are getting married, having children, living independently from their parents, buying homes, and achieving financial independence. Nearly one in five young adults ages 25 to 29 are disconnected from work and school. A growing share of young adults carry high levels of student loan and credit card debt that may cause them to postpone marriage and family formation.1 The pandemic will likely amplify these trends.

The statistics are grim. More than 40 million workers filed for unemployment benefits in the spring of 2020. Millions of young adults work in restaurants and other service-sector jobs that have been heavily affected by stay-at-home orders and social distancing measures. The pandemic is also exacerbating the wide economic disparities between whites and other groups—especially Blacks and Latinos—who are more likely to be working in low-wage jobs with few benefits.

The current health and economic crisis is unprecedented, making it difficult to predict the impact on patterns of marriage, childbearing, homeownership, and living arrangements of young adults in the coming months and years. But we can look back at recent trends for clues.

The Coronavirus Could Prompt Many to Postpone Marriage

While the Great Recession may have forced some young adults to postpone key life transitions—such as finding a full-time job or buying a home—the decline in the proportion who are married is a longer-term trend that predates the economic downturn. It’s hard to gauge whether the decline in marriage during the recession was due to economic factors or just a continuation of previous trends.

The coronavirus may be different. In the short term, it will force millions of young adults to consider postponing marriage until social distancing restrictions are lifted. Longer-term effects on marriage are more difficult to predict.

On the one hand, some young adults—particularly those with less education and lower incomes—may decide to postpone marriage until the economy recovers, which could take years. The “economic prerequisites for entering marriage are higher today than they were for previous generations.”Meeting those requirements—finding a job, achieving some financial independence, accumulating some savings, and perhaps buying a home—may be harder than ever in the current environment, especially for lower-income workers without college degrees.3

The decline in the proportion married among young adults with lower levels of education accelerated during the Great Recession and has continued over the past decade (see Figure 1). The proportion of college graduates who are married has also declined but at a slower pace, which has led to a growing marriage gap between those at different education levels.4

FIGURE 1. Share of Young Americans Ages 25 to 34 Who Are Married (Spouse Present), by Educational Attainment, 2000-2025

Note: Projections are calculated by applying the average rate of change during the Great Recession and its aftermath to future years.
Source: IPUMS-Current Population Survey, University of Minnesota, www.ipums.org.

Between 2000 and 2019, the proportion of young adults without bachelor’s degrees who were married dropped 16 percentage points to 37%. But for college graduates, the proportion dropped just 10 percentage points to 46%. The fallout from the coronavirus could exacerbate the marriage gap for people at opposite ends of the education ladder.

If patterns since the Great Recession continue, about one-third (32%) of young adults without bachelor’s degrees may be married by 2025, compared with 42% of young adult college graduates.

On the other hand, marriage provides an opportunity to pool resources and offers tax and health coverage benefits that may be attractive to some young adults who were on the fence about tying the knot.5 A key factor contributing to the recent decline in marriage rates, especially for less-educated groups, has been the rise in women’s earnings relative to men.6 As women’s wages have increased, fewer women have relied on a spouse or partner to provide a paycheck. However, the current economic crisis may disproportionately affect women, who are more likely to be employed in service-sector jobs. A rise in “marriageable men” relative to women could potentially lead to an increase in the proportion of young adults who marry in the coming years.7

Cohabitation Expected to Increase Among Young Adults

As marriage rates among young adults have declined in recent years, cohabitation rates have increased, either as a precursor to or substitute for marriage.

The share of young women ages 25 to 34 living with a partner more than doubled between 2000 and 2019, from 7% to 22% (see Figure 2). For men, cohabiting increased from 8% to 19% during the same period. The share of young adults who have ever cohabited is much higher and increasing. In 1995, nearly half (49%) of women ages 25 to 29 had ever cohabited, but that share rose to 73% in 2011 to 2013.8

FIGURE 2. Share of Young American Men and Women Ages 25 to 34 Living With a Cohabiting Partner, 2000-2025

Notes: A change in methods used to identify cohabiting couples accounts for part of the increase in cohabitation in 2007. Projections are calculated by applying the average rate of change during the Great Recession and its aftermath to future years.
Source: U.S. Census Bureau, Current Population Survey.

Cohabiting relationships in the United States tend to be short, with most couples breaking up or getting married within a few years. Serial cohabitation—a pattern of multiple, nonmarital cohabiting relationships—is also increasingly common, especially among couples with lower levels of education.9

Will more young adults choose to live together because of the coronavirus pandemic’s impact on the economy? In the short term, anecdotal evidence suggests that social distancing measures have “fast-tracked many relationships” among couples forced to choose between living separately indefinitely and moving in together.

Other couples may decide to postpone cohabiting until economic prospects improve. Population Reference Bureau projections indicate that the share of young adult women and men who are cohabiting could rise to 22% and 19%, respectively, by 2025.

U.S. Fertility Rate Is at a Record Low and Could Fall Even Further

Some have speculated that the coronavirus pandemic will lead to a baby boom, with so many couples stuck at home due to social distancing requirements. But the research suggests otherwise.

The U.S. total fertility rate (TFR) has declined during previous economic downturns, and the current economic crisis will likely have a similar impact on births. The TFR fell to low levels during the Great Depression in the 1930s, amid the 1970s oil shock, and with the Great Recession in 2007. Fertility in the United States recently dropped to the lowest level in recorded history, with women having an average of 1.7 births in their lifetime.

The timing of childbearing has also changed. Delays in marriage have in turn resulted in delays in first births. In 2018, the average age of first-time mothers was 27, up from 25 in 2000. By 2016—for the first time in U.S. history—the birth rate among women ages 30 to 34 (103 births per 1,000 women) exceeded that of women ages 25 to 29 (102 births per 1,000 women) (see Figure 3).

FIGURE 3. U.S. Births per 1,000 Women, by Age Group, 2000-2025

Note: Projections are calculated by applying the average rate of change during the Great Recession and its aftermath to future years.
Source: U.S. Centers for Disease Control and Prevention, National Center for Health Statistics.

The economic impact of the coronavirus may cause more young adults to postpone births, leading to further declines in birth rates, especially among women under age 30.

States like Nevada, which relies heavily on tourism, may see bigger declines in fertility than states with more diversified economies. Fertility declines during the Great Recession were greatest in states most impacted by the economic downturn.10

Homeownership Among Young Adults Has Dropped Sharply Since 2007

Searching for a home right now is challenging because of social distancing guidelines, but the longer-term effects of the coronavirus on the housing market could linger for years. Millions of Americans who have been temporarily or permanently laid off may lose income and have to dip into their savings, decreasing their ability to secure a loan or make a down payment on a house. Many existing homeowners may need to sell their homes to help pay the bills.

The homeownership rate among young adults declined with the onset of the subprime mortgage crisis in 2007 and has continued to drop (see Figure 4). Between 2007 and 2019, householders ages 65 and older experienced a modest decline in homeownership (1 percentage point), whereas rates dropped sharply for householders ages 25 to 34 (8 percentage points) and 35 to 64 (9 percentage points).

FIGURE 4. U.S. Homeownership Rates by Age of Householder, 2000-2025

Note: Projections are calculated by applying the average rate of change during the Great Recession and its aftermath to future years.
Source: IPUMS-Current Population Survey, University of Minnesota, www.ipums.org.

Historically, young adults (ages 25 to 34) have had lower homeownership rates than adults ages 65 and older, and the gap between these two groups has increased 4 percentage points from 2000 to 2019. By 2025, this gap could grow even wider, according to PRB’s projections. By 2025, just 34% of householders ages 25 to 34 may be homeowners, compared with 80% of householders ages 65 and older.

Although this trend may suggest a change in housing preferences, more than two-thirds of renters report that they would buy a home if they had the financial resources to do so.11 The decline in homeownership has also been linked to lower rates of marriage and family formation among young adults.12 The share of young men and women ages 25 to 34 living with a spouse dropped from 50% and 57%, respectively, in 2000 to 36% and 45%, respectively, in 2019.13

Wide gaps in homeownership rates also persist across different racial and ethnic groups. During the housing market crisis, owning a home became a liability for many Americans but especially for African Americans and Latinos, who were more likely to have high-cost or subprime mortgages. Black and Latino workers were disproportionately low income prior to the coronavirus pandemic, and the current economic crisis could further impact the ability of Black and Latino young adults to qualify for loans or make their mortgage payments in the coming months.

More Young Adults Are Expected to Live With Parents

Declines in marriage have been accompanied by an increase in young adults—especially men—returning to or remaining in their parents’ homes, and the coronavirus pandemic will likely intensify this trend.

Between 2000 and 2019, the share of young men ages 25 to 34 living with their parents rose from 12% to 22% (see Figure 5). The share of young women living with their parents increased from 8% to 15% during the same period. For both men and women, the proportion who were doubling up with their parents in 2019 was at or near the highest levels since the U.S. Census Bureau first started tracking the measure in 1960.

FIGURE 5. Share of Young American Men and Women Ages 25 to 34 Living With Their Parents, 2000-2025

Note: Projections are calculated by applying the average rate of change during the Great Recession and its aftermath to future years.
Source: U.S. Census Bureau, Current Population Survey.

The rising number of young adults living with their parents, often disconnected from work and school, may lead to further declines in marriage, family formation, and childbearing. About 22% of young men and 15% of young women are projected to be living in their parents’ homes by 2025.

The Effects of the Coronavirus Could Last for Decades

The coronavirus pandemic could be the most significant event that will occur in our lifetime and will likely have long-lasting effects on marriage, family formation, poverty, and health in the United States. Some have pointed to the positive effect of the pandemic on bringing families together, but researchers have also shown that entering the job market during a period of economic turmoil can have long-term, negative consequences for young adults. In midlife, they earn less (while working more), are less likely to be married, are more likely to be childless, and are more likely to die prematurely compared with young adults who enter the workforce during a healthier economy.14 Young adults who entered the job market during the Great Recession are still feeling the impact.

Blacks and Latinos have been disproportionately affected by layoffs due to the pandemic, and the negative effects on Black and Latino young adults will likely linger for years—exacerbating long-standing social, economic, and health inequalities between whites and other racial/ethnic groups.

Right now, life is on hold for millions of Americans. We cannot predict the long-term effects of this crisis, but it’s likely that young adults will be severely impacted by the economic fallout. Making sure these young adults have the resources they need to cover their basic needs and access educational, employment, and training opportunities—both during and after the pandemic—will be an ongoing challenge for federal, state, and local policymakers for many years.

Empty college dorm room

Coronavirus and the 2020 Census: Where Should College Students Be Counted?

UPDATE: 2020 Census operations are changing in response to the coronavirus pandemic. The U.S. Census Bureau announced on June 18, 2020, that it is reaching out to colleges and universities with significant off-campus student populations to help ensure they are counted in the right place in the 2020 Census. College and university presidents have been asked to provide roster and basic demographic information already provided to the university for off-campus students. This information allows the Census Bureau to count the students where they would have been staying on April 1, 2020, even if they went home early due to a school closure or shift to distance learning. It can also be used to remove duplicate responses to the census or to count students (if there is no other record of the same individuals in another location). Census Bureau staff began calling school officials on June 16.


Just as the 2020 Census is getting underway, many colleges and universities across the country are closing their campuses and moving classes online in response to concerns about the coronavirus and the disease it causes, COVID-19.

Where should college students be counted in the 2020 Census? Census Bureau officials say students living away from home should be counted at their on-campus or off-campus college address, even if coronavirus has temporarily sent them to stay with their parents or elsewhere.

Most of the students moving out of their on-campus dorms and residence halls won’t return until after Census Day, which is April 1, 2020. While some students living off-campus may choose not to leave, many are returning to their prior residence (such as a family home) during these campus closures.

According to the Census Bureau’s Official Residence Criteria for the 2020 Census, college students will be counted at their “usual residence” on April 1, 2020 or where they live and sleep “most of the time.”

This means that college students will be counted at their college address (either on- or off-campus), even if they are staying at their parents’ or guardians’ home on Census Day while on break, vacation, or due to COVID-19 closures. An accurate count of students—temporarily displaced due to the pandemic—is critical for towns and cities that are home to large numbers of college students. Student populations factor into disaster planning and emergency response, public health analysis and planning, infrastructure planning, government funding allocations, and many more policy and program decisions.

How Do Colleges Count Students Living On-Campus?

Every college or university is responsible for providing the Census Bureau with a total count of students living in university-run housing, which may include fraternities and sororities.

Many schools transmit this information electronically using their housing administrative records. Some, however, opt to distribute Individual Census Questionnaires to students, who complete them and return them to the school, which passes the completed forms to a Census Bureau enumerator. With many campuses closed due to COVID-19, the Census Bureau will be reaching out to those schools and inviting them to switch to the electronic option.

Either way, it is the responsibility of the college or university to gather the necessary information and provide it to the Census Bureau. Students living in on-campus or in university-run housing should not complete the census online or by telephone.

If a student living on-campus or in university-run housing is unsure about what to do regarding the 2020 Census, they should contact their college’s housing administration office or the Census Bureau.

Students Living Off-Campus Should Be Counted at Their Off-Campus Address

Students who live in off-campus housing with or without roommates should be counted as if they were still living there on April 1, even though they may have returned “home” at the urging of the school or public health authorities. As with students living on-campus, students living off-campus should not be included on their parents’ or guardians’ census form.

Students opting to leave their college-area residence to return home will likely not be there to receive the census materials that are being mailed to them by the Census Bureau. In this situation, students should use the address of their college-area residence and follow the Census Bureau instructions for Responding to the 2020 Census without a Census ID number.

Students who live with others in off-campus residences should coordinate with their roommates to ensure that only one questionnaire is completed for their household. Whoever completes the census questionnaire for the household should list all roommates, including non-students, who live and sleep at that address most of the time.

College students living outside of the United States on Census Day due to study abroad or other programs are not counted in the census. College students who are foreign citizens living and attending college in the United States should be counted at their on- or off-campus address in the same way as their U.S. counterparts.

To help ensure an accurate count, the Census Bureau is asking colleges and universities to contact their students and remind them to respond to the 2020 Census.

How Are Census Residency Rules for COVID-19 Different From Other Natural Disasters?

Some disasters—such as the wildfires in Paradise, California or Hurricane Maria in Puerto Rico—destroy homes. In these types of disasters, returning is uncertain, even for people who plan to rebuild. During pandemic-related college closures, students have only been displaced temporarily, there is no change in available housing, and students will return when schools reopen.

For more information, see the Census Bureau’s Statement on Modifying 2020 Census Operations to Make Sure College Students Are Counted.

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How Demographic Changes Make Us More Vulnerable to Pandemics Like the Coronavirus

The world is better equipped to fight a pandemic today than it was in 1918, when influenza swept the globe and infected up to one-third of the world’s population.1 While science and medical advances have given us new advantages in fighting disease, some demographic trends since 1918 may increase the risk for spreading contagions and our vulnerability to viruses.

Population Mobility Allows Viruses to Spread Quickly Around the World

The sheer volume of today’s population movements—from migration and travel as people fly within and across countries—may make it faster and easier for viruses to spread around the world.

During the 1918 flu pandemic, the airline industry was not yet established, and overseas travel was expensive and time consuming. Even with these limitations, the flu spread across multiple countries in a matter of months, mainly because of the large number of military personnel returning home from World War I (1914-1918).2

Since then, flight has become so established in our society that it’s commonplace. By 2018, the global airline industry had 4.3 billion scheduled passengers, up from 1.3 billion passengers in 1995. Similarly, international tourist visits globally have nearly doubled in the past decade, from 936 million visits in 2009 to 1.8 billion visits in 2018.3

The increased volume of travel—both international and domestic—presents a significant challenge to stopping or slowing the spread of the coronavirus and COVID-19, the disease caused by the virus. China’s first reported COVID-19 case occurred in December 2019, and Thailand reported its first confirmed case on Jan. 13, 2020. One week later, by January 20, South Korea and Japan also reported their first cases.4 More than 20 countries reported COVID-19 cases by the end of that month.5

As of April 7, 2020, more than 1.5 million cases of COVID-19 were confirmed across 183 countries and territories.6 For many of these countries, their initial cases developed from travelers from China (such as in Thailand, South Korea, Japan, and Italy) or, later, from travelers from other countries then experiencing an outbreak. Several countries in Europe reported their first cases originating with travelers from Italy, which has been one of the first and hardest hit countries in Europe.7

In the United States, the epicenter for the pandemic is New York City, a densely populated megacity with many international travelers. The first confirmed case in the city came from a traveler who had returned to the city from overseas.8

Population Density in Urban Areas Can Heighten Disease Transmission

As data from tracking the coronavirus shows, once a virus arrives somewhere, it can spread quickly within populations. One key factor to this spread is urbanization.

Population density has generally increased because of the quadrupling in the global population since the 1920s to the current 7.7 billion, but we’re more concentrated in urban areas today than we were back then—more than half the world’s population lives in urban areas.9 Between 1920 and 2020, the percent of the world population estimated to be living in urban areas increased from around 20% to 56%.10 This growth has been largest in Asia and Africa, where their shares are currently 51% and 41% respectively, around three times their percentages in 1950.11

The number of large cities has also soared: 548 cities had 1 million or more people in 2018, a nearly 50% increase from 371 cities in 2000, and a more than seven-fold increase from 77 cities in 1950. In 1950, only New York and Tokyo with their surrounding metropolitan areas were considered megacities, with a population of at least 10 million. By 2018, this number increased to 33, with 27 megacities in developing countries. China is home to six megacities, and India has five megacities. All except one of the 10 cities projected to become megacities between 2018 and 2030 are in developing countries.

The growth in and location of megacities is significant when considering public health crises like those posed by the coronavirus pandemic. While population density facilitates the spread of diseases even in developed countries, rapid urbanization in developing countries—often without proper planning—can result in unsafe crowding and areas with concentrated poverty (slums). This overcrowding and lack of infrastructure for sanitation and hygiene provide prime conditions for the spread of many diseases. Air pollution in large cities also weakens lung function, which may make residents more vulnerable to COVID-19.12

As population growth and urbanization continue, they generate another way in which a virus may spread more easily: As human settlements expand, animal habitats often shrink or are destroyed, increasing the risk of humans coming into contact with new animal-born disease vectors, as scientists believe is the case for the coronavirus (and is the case with many epidemics).

Population Aging Means More Older People Are at Risk of Infection

While the demographic changes in population movement and urbanization may make it easier for viruses to spread, population aging makes us more vulnerable to them. The number of older adults ages 60 and older globally has increased five-fold from 202 million to 1.05 billion between 1950 and 2020, while the total population increased three-fold.13 Coupled with declines in fertility rates during the same period, the result is a rapid aging of the global population—the share of the older population ages 60 and older has increased from 8% in 1950 to 13.5% in 2020.14

The likelihood of becoming severely ill with COVID-19 appears to be greater among those ages 60 and older. While people of all ages can become infected with the coronavirus, older adults may be more at risk partly because they’re more likely to have one or more noncommunicable diseases reported to increase vulnerability, such as cardiovascular diseases, cancers, diabetes, and chronic respiratory diseases, PRB reports.

The age pattern of mortality indicates that places with more older adults are likely at risk of higher rates of severe illness or death than places with younger populations, if all else remain the same, PRB researchers explain. The case fatality rate from COVID-19 in China among those ages 80 and older is reported to be six times higher than the overall case fatality rate for that country.15

Italy’s population has been particularly hard hit by the coronavirus. It began with three cases in people who had traveled from China. Although social distancing is considered to have helped slow the spread in Italy, the country has suffered a significant number of deaths—nearly 18,000 as of this writing—partly because Italy’s population ranks as the oldest in Europe.

Sixteen percent of Italy’s population is ages 85 and older. That segment of the population—those age 85 and older, the group often referred to as the oldest-old—is the fastest-growing age group globally, increasing from less than 5 million people to 64 million people between 1950 and 2020.

The first confirmed case of COVID-19 in the United States was found with a man returning from Wuhan, China, to the state of Washington. It then quickly spread to elderly residents living in close quarters at a nearby nursing home, many of whom have underlying conditions and weakened immune systems. The disease claimed the lives of 35 people less than one month after the first patient was transferred to a hospital.

Demographic Changes Must Be Considered When Evaluating New Health Threats

These facts illustrate how demographic trends in the global mobility of populations, urbanization and population density, and longevity and population aging have likely made us more vulnerable to the coronavirus pandemic and pandemics in general.

Such demographic changes are important to consider as countries evaluate their risks for experiencing pandemics like the coronavirus or other infectious diseases and work to develop new ways to protect their populations. For example, decisionmakers can identify the areas with populations most vulnerable to a disease and increase stocks of protective gear like masks and hand sanitizers; medical supplies such as ventilators, surgical gowns, gloves, and face shields; and hospital beds.

Policymakers may also want to consider policies such as paid sick leave and enhanced unemployment benefits for wage workers in service industries and other industries where workers come into regular contact with the public. These policies will both cut down on the spread of the virus and ease the financial burden on individuals and the economic impact on society.

References

 

  1. Centers for Disease Control and Prevention, “History of the 1918 Flu Pandemic,” https://www.cdc.gov/flu/pandemic-resources/1918-commemoration/1918-pandemic-history.htm.
  2. “Influenza Pandemic of 1918-19,” Encyclopedia Britannica, updated March 20, 2020, https://www.britannica.com/event/influenza-pandemic-of-1918-1919.
  3. Smithsonian National Air and Space Museum, “America by Air: Airline Expansion and Innovation 1927-1941” (2007), https://airandspace.si.edu/exhibitions/america-by-air/online/innovation/innovation15.cfm.
  4. World Health Organization, “Novel Coronavirus (2019-nCoV) Situation Report – 1,” Jan. 21, 2020, https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.
  5. World Health Organization, “Novel Coronavirus (2019-nCoV) Situation Report – 12,” Feb. 1, 2020, https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.
  6. Johns Hopkins University & Medicine, “COVID-19 Map,” Coronavirus Resource Center (2020), https://coronavirus.jhu.edu/map.html.
  7. Derrick Bryson Taylor “A Timeline of the Coronavirus Pandemic,” The New York Times, updated April 2, 2020, https://www.nytimes.com/article/coronavirus-timeline.html.
  8. Carl Zimmer, “Most New York Coronavirus Cases Came From Europe, Genomes Show,” The New York Times, April 8, 2020, https://www.nytimes.com/2020/04/08/science/new-york-coronavirus-cases-europe-genomes.html.
  9. United Nations, Department of Economic and Social Affairs (UNDESA), Population Division, 2018 World Urbanization Prospects (2018), https://population.un.org/wup/.
  10. UNDESA, “Growth of the Urban and Rural Population, 1920-2000,” Population Studies, no. 44 (1969), https://population.un.org/wup/Archive/Files/studies/United%20Nations%20(1969)%20-%20Growth%20of%20the%20World%27s%20Urban%20and%20Rural%20Population,%201920-2000.pdf; UNDESA, Population Division, 2019 World Population Prospects (2019), https://population.un.org/wpp/.
  11. UNDESA, 2018 World Urbanization Prospects.
  12. Xiao Wu et al., “Exposure to Air Pollution and COVID-19 Mortality in the United States,” medRxiv, April 7, 2020, https://doi.org/10.1101/2020.04.05.20054502.
  13. UNDESA, 2019 World Population Prospects.
  14. UNDESA, 2019 World Population Prospects.
  15. Nurith Aizenman, “Why the Death Rate From Coronavirus Is Plunging in China,” NPR, All Things Considered, March 3, 2020, https://www.npr.org/sections/goatsandsoda/2020/03/03/809904660/why-the-death-rate-from-coronavirus-is-plunging-in-china.

 

prb-hero

Supporting Coronavirus Outreach in Sub-Saharan Africa

Product: Videos

Author: Population Reference Bureau

Date: April 13, 2020

Partner: Cadres des Religieux pour la Santé et le Développement (CRSD)

All Together Against COVID 19 (Tous ensemble contre la COVID 19)

All Together Against COVID 19 (Tous ensemble contre la COVID 19) Video thumbnail

All Together Against COVID 19 (Tous ensemble contre la COVID 19)

Tous ensemble contre la COVID 19 (Wolof) Video thumbnail

Tous ensemble contre la COVID 19 (Wolof)

In response to the coronavirus pandemic, PRB is supporting partners and others by providing information and resources to help communities stay safe. These videos, produced for our partner, Cadres des Religieux pour la Santé et le Développement (CRSD), encourage faith communities in the Sahel region of Africa to worship at home and to adopt other practices to stem the spread of the virus in that region.

motion chefs  of a restaurant kitchen

Workers at Risk During the Coronavirus Pandemic: Four in 10 Food Preparers and Servers Are Low-Income

The coronavirus pandemic sweeping the globe in 2020 will have long-term and widespread effects on the U.S. economy and labor force. A PRB analysis finds that workers in one of the hardest-hit sectors—food preparation and server-related occupations—are among the most economically vulnerable.

Food preparers and servers include cooks, waitstaff, and others who help prepare and serve our meals in restaurants, coffee shops, hospitals, and school cafeterias. As businesses begin to reopen, the economic challenges facing lower-income workers may have a negative ripple effect. Financial pressures may compel people to work when sick, and those who are uninsured may delay or avoid seeking care for an illness.

In 2018, the United States had 8.8 million food preparers and servers, and more than four in 10 of them (41%) were low-income, meaning they had family incomes below 200% of the official poverty threshold ($50,930 for a family with two adults and two children). Nationwide, 19% of workers were low-income in 2018 (see table).

TABLE. Low-Income Status of U.S. Workers in Selected Occupations, 2018

wdt_ID Occupations Total Workers Low-income Workers Percent Low-Income
1 All occupations 155,982,549.0 30,059,749.0 19
2 Food preparers and servers 8,803,519.0 3,596,843.0 41
3 Personal care and service workers 4,404,322.0 1,388,299.0 32
4 Sales workers 15,709,547.0 3,432,743.0 22

Notes:Families with incomes below 200% of the official poverty threshold are classified as low-income. These estimates are subject to both sampling and nonsampling error.
Source:PRB analysis of data from the U.S. Census Bureau’s American Community Survey Public Use Microdata Sample (PUMS).

Food preparers and servers face additional challenges:

  • A high housing cost burden: In 2018, more than three in 10 workers in food preparation and server-related occupations (31%) had a high housing cost burden—defined as spending more than 30% of household income on housing costs such as mortgage or rent payments, utilities, and other expenses. The national average for all workers was 20%. (Housing costs can impact household composition, as PRB reports.)
  • Lack of health insurance: About 21% of food preparers and servers lacked health insurance coverage in 2018—more than double the national average (10%). Health insurance coverage is important not only so low-income families have access to affordable health care when they need it, but also because persistent health issues and chronic conditions can affect their ability to work and provide for their families.
  • Very low pay for unskilled workers: Among workers in restaurants and other locations that serve meals, dishwashers are among the most economically vulnerable. In 2018, more than 300,000 people worked as dishwashers in the United States, and nearly half of them (49%) were low-income. Chefs and head cooks were among the least likely to be low-income, at 28%.

African Americans and Native Americans Are More Likely to Be Low-Income

The novel coronavirus is affecting people across the nation, but African Americans and Native Americans are among the most economically vulnerable populations, as PRB notes in an analysis. Those who work in food preparation and server-related occupations are particularly vulnerable (see Figure 1). In 2018, over half of African American food preparers and servers were low-income, compared with 37% of white workers in those jobs. American Indians/Alaska Natives also had a high share of food preparers and servers who were low-income (49%).

FIGURE 1. Low-Income Status of Food Preparers and Servers and All Workers, by Race/Ethnicity, 2018

wdt_ID Risk Status, 2014-2018 Number of Young Children Percent of Young Children
1 Low risk of undercount or potential overcount 3,095,045.0 19
2 High risk of undercount 9,290,040.0 56
3 Very high risk of undercount 4,065,149.0 25
4 Total 16,450,234.0 100

Note: Individual racial groups include only single-race non-Hispanics. Hispanics/Latinos
may be of any race. Families with incomes below 200% of the official poverty threshold are classified as low-income. These estimates are subject to both sampling and nonsampling error.

Source: PRB analysis of data from the U.S. Census Bureau’s American Community Survey PUMS.

Workers in the South Are More Likely to Be Low-Income

Food preparers and servers are faring better in some states than others (see Figure 2). In three states—Hawaii, New Hampshire, and Rhode Island—fewer than 30% of workers in food preparation and server-related jobs were low-income in 2018. Food preparers and servers were most likely to be low-income in Arkansas and Mississippi, at more than 55% each. In general, states in the South have higher shares of low-income workers than states in other regions.

FIGURE 2. Food Preparers and Servers Who Are Low Income, 2018


Note: Families with incomes below 200% of the official poverty threshold are classified as low-income. These estimates are subject to both sampling and nonsampling error.
Source: PRB analysis of data from the U.S. Census Bureau’s American Community Survey PUMS.

Personal Service and Sales Workers Are Also Vulnerable

Personal care and service workers—including child care workers, personal and home care aides, workers in hotels and casinos, fitness instructors, and others—are also expected to be hit hard by lost wages and unemployment stemming from the coronavirus pandemic. In 2018, the United States had 4.4 million personal care and service workers and 32% were low-income. Salespeople, also at high risk of layoffs and lost earnings, make up a larger group of workers—15.7 million in 2018—but were less likely to be low-income, at 22%.

In combination, food preparers and servers, personal care and service workers, and salespeople make up 28.9 million workers, or about 19% of the total U.S. workforce. Yet they account for 28% of all workers who are low-income.

Policymakers Can Help COVID-19-Affected Workers and Businesses

Low-income workers face significant challenges—including housing stability and access to affordable health care and child care—under normal circumstances. The pandemic crisis puts these workers at a double disadvantage. Lack of health insurance may discourage low-income workers from seeking health care when they need it, and treatment may result in medical debt. The risk of lost wages may lead people to go to work when sick, increasing the health risk for others. Workers who are laid off due to illness or government-imposed distancing measures may not have enough money to meet basic needs, including food and housing.

Policymakers can help by providing direct cash transfers to affected workers and the businesses that employ them. Some jurisdictions and service providers are also implementing moratoria on evictions and utility shut-offs, and making other accommodations to address the COVID-19 crisis. By providing an adequate safety net for workers who are most economically affected by the pandemic, policymakers can improve the economic outlook for millions of people and speed the recovery of the U.S. economy.


More information about the economic divide between working families at the top and bottom of the economic ladder is available in Low-Income Working Families: Rising Inequality Despite Economic Recovery, by Beth Jarosz and Mark Mather.

 

Multi-Generation African hispanic family at home

U.S. Household Composition Shifts as the Population Grows Older; More Young Adults Live With Parents

Household size and composition play an important role in the economic and social well-being of families and individuals. The number and characteristics of household members affect the types of relationships and the pool of economic resources available within households, and they may have a broader impact by increasing the demand for economic and social support services. For example, the growth in single-parent families has increased the need for economic welfare programs, while a rising number of older adults living alone has led to greater demand for home health care workers and other personal assistance services. The decennial census provides the most comprehensive and reliable data on changing household size and composition, especially for less numerous household types such as same-sex married couples.

A Reversal of the Long-Term Decline in Household Size?

Average household size has declined over the past century, from 4.6 persons in 1900 to 3.68 persons in 1940 to only 2.58 persons by 2010.1 This decline is due to decreases in the share of households with three or more persons and increases in the share with only one or two persons. In 1940, for example, more than one in four households (27 percent) had at least five persons and less than one in 10 (8 percent) had only one person.2 By 2010, these shares had nearly reversed, with more than one-fourth of all households (27 percent) having only one person and slightly more than one-tenth (11 percent) having five or more persons.3

However, there are signs of a reversal in the decline in average household size. Although the trend away from large households has continued since 2010, average household size actually increased between 2010 and 2017 from 2.58 to 2.65 persons.4 If average household size remains larger than 2.58 in 2020, it will be the first such intercensal increase since the 1900 Census. The increase in average household size since 2010 appears to be driven by growth in the share of households with two persons—from 33 percent to 34 percent—and a decline from 40 percent to 38 percent in the share with three or more persons. Changes in household composition help explain these trends in household size.

Household Composition Continues to Shift From Family to Nonfamily Households

The shifts in U.S. household composition over the last five decades have been striking, as the share of family households has declined and the share of nonfamily households has increased. In 1960, 85 percent of all households contained families, but by 2017, this share had dropped to 65 percent (see Table). Conversely, the share of nonfamily households more than doubled from 15 percent to 35 percent during this period. The types of households within the family and nonfamily categories have also shifted, with a consistent decline in the share of married couples with children and a steep and consistent increase in the share of people living alone. Since 1960, the shares of single-parent families and other nonfamily households more than doubled.

TABLE. Share of Households With People Living Alone, Single-Parent Families Increases While Share of Married-Couple Households With Children Declines

wdt_ID Household Type 1960 1980 2000 2010 2020
1 Family Households 85 74 68 66 65
2 Married Couples w/ children 44 31 24 20 19
3 Married Couples w/out children 31 30 28 28 30
4 Single Parents w/ children 4 7 9 10 9
5 Other Family 6 6 7 8 9
6 Nonfamily Households 15 26 32 34 35
7 One Person 13 23 26 27 28
8 Other Nonfamily 2 4 6 7 7

Note: Percentages may not sum to 100 due to rounding.
Sources: James A. Sweet and Larry L. Bumpass, American Families and Households, Table 9.2 (New York: Russell Sage Foundation, 1987); U.S. Census Bureau, 2000 and 2010 decennial censuses; 2017 American Community Survey.

The Share of Married-Couple Households With Children Has Declined

In 1960, married-couple families made up 75 percent of all U.S. households, and 44 percent of these families had children. Single-parent families made up only 4 percent of all households, and other families accounted for 6 percent. By 1980, a significant shift in the composition of family households was underway. Married-couple families made up only 61 percent of all households, and the share with children dropped to 31 percent. The share of single-parent families nearly doubled from 4 percent to 7 percent of all households, while the share of married-couple families without children remained about the same at 30 percent.

Since 1980, the pace of change has slowed but the transformation of family households has continued. By 2017, married-couple families accounted for less than half of all households, and only about one-fifth (19 percent) of households were married couples with children. The share of married-couple families without children also declined slightly to 28 percent between 1980 and 2010, but increased to 30 percent between 2010 and 2017—almost back to the 1960 level of 31 percent. In contrast, the share of single-parent families continued to increase after 1980, rising to 10 percent by 2010, while the share of other families rose from 6 percent to 9 percent of all households by 2017.

The Share of One-Person Households Has Increased

In 1960, only 15 percent of all U.S. households were nonfamily households, and 13 percent were one-person households. Over the next 20 years, nonfamily households underwent dramatic shifts: The share of one-person households jumped to 23 percent, and the share of other nonfamily households doubled to 4 percent. The rapid growth in one-person households was largely due to increases in the share of older adults living alone, particularly women. The share of women ages 65 and older who lived alone rose from 23 percent in 1960 to 37 percent in 1980.5

The share of nonfamily households continued to rise after 1980, but at a slower pace. By 2017, more than one-third (35 percent) of all households were nonfamily households, and more than one-fourth (28 percent) were one-person households. The share of other nonfamily households also increased after 1980, reaching 7 percent by 2010. Beginning in the 1980s, the rise in cohabitation contributed to the growth in two-person nonfamily households; unmarried partners made up almost all of the households in this category in 2010. The share of other nonfamily households has not changed since 2010.

Household and Family Type Vary Widely Across Age Groups

Household composition varies among householders in different age groups and reflects the sequence of life-cycle stages that individuals experience as they age—from moving out on their own to marriage and family formation to empty nest to retirement. Changes in the share of householders in different age groups have contributed to shifts in household composition in the United States.

Most young adult householders in the United States live alone or with roommates. Three-fifths (61 percent) of households headed by an adult under age 25 were nonfamily households in 2017, while only 39 percent were family households (see Figure 1). One-third (33 percent) of householders under age 25 lived with unrelated roommates—including cohabiting partners—while an additional 28 percent lived alone. Only a small share (15 percent) headed married-couple families with or without children, but 14 percent of householders under age 25 headed single-parent families in 2017.

FIGURE 1. More Than Eight in 10 Older Adult Householders Are Living Alone or Are Empty Nesters, While Over Half of Young Adult Householders Live Alone or With Roommates

article4-fig1@4x

Percent Distribution of U.S. Household Types by Age of Householder, 2017

Notes: Percentages may not sum to 100 due to rounding. Among householders ages 65 and older, 0.4 percent headed married-couple households with children and 0.1 percent headed single-parent households with children.
Sources: U.S. Census Bureau, 2017 American Community Survey Public Use Microdata Sample (PUMS).


In contrast, the split between family and nonfamily households is reversed among householders ages 25 to 44—only 28 percent headed nonfamily households and 72 percent headed family households. While only one-fifth of households headed by an adult under age 25 included children, almost three-fifths (56 percent) of householders ages 25 to 44 headed families with children—both married-couple families (38 percent) and single-parent families (19 percent). Only 11 percent headed married-couple families without children. About one-fifth (19 percent) of householders in this age group lived alone in 2017, but less than one in 10 (9 percent) headed 2+-person nonfamily households—down from 33 percent among householders under age 25.

More than a third of householders ages 45 to 64 (37 percent) were empty nesters, heading married-couple households without children. Only about one-fifth (21 percent) of householders ages 45 to 64 headed families with children—16 percent were married-couple families and only 6 percent were single-parent families. However, a relatively high share of householders ages 45 to 64 were heading other family households (11 percent) and one-person households (26 percent).

Eight in 10 householders ages 65 and older were either heading married-couple families without children (44 percent) or living alone (42 percent). Only 10 percent of householders in this oldest age group headed other family households and only 3 percent headed other nonfamily households.

What’s Driving Changes in Household Composition?

Beginning in the 1960s—and accelerating over the last two decades—changes in marriage, cohabitation, and childbearing have played a key role in transforming household composition in the United States. More recently, population aging and shifts in the age distribution of householders are also contributing to these changes in composition.

Young Adults Continue to Delay Marriage and Childbearing

Delays in marriage and childbearing and increases in cohabitation among young adults have contributed to the decline in the share of family households—particularly married couples with children—and the steep rise in the share of nonfamily households. The median age at first marriage reached a new high in 2017—29.5 for men and 27.1 for women—and cohabitation rates have continued to increase.6 In 2011-2013, 65 percent of women ages 19 to 44 reported having had a cohabiting relationship, up from 33 percent in 1987.7

Birth rates among women under age 30 have continued to decline since 2010, although the rates for women ages 30 to 34 increased through 2016 before decreasing from 2016 to 2017.8 The share of births to women under age 40 that occurred outside of marriage increased from about 21 percent in 1980-1984 to 43 percent in 2009-2013; about 60 percent of the nonmarital births in 2009-2013 were to cohabiting couples—up from only 28 percent in 1980-1984.9

Between 2000 and 2010, the increase in cohabiting couples with children contributed to growth in the shares of both single-parent families and other nonfamily households due to the ways the Census Bureau classifies such couples by household type. However, between 2010 and 2017, the share of other nonfamily households stayed constant, and the share of single-parent families declined slightly from 10 percent to 9 percent. This decrease may be due to the drop from 18 percent to 14 percent in the share of householders under age 25 who were heading single-parent families. While declining birth rates among young women are partly responsible, this decline could also be related to more young couples with children living with their parents rather than in their own households. This explanation is supported by evidence of an increase in the number of multigenerational households, which rose from 4.4 million in 2010 to 4.6 million in 2017.

A Growing Share of Householders Are Ages 65 and Older

As fertility rates have fallen and baby boomers have aged, the distribution of the adult population ages 18 and older in the United States has shifted to older age groups. Between 2010 and 2017, the share of adults ages 45 to 64 declined from 35 percent to 33 percent, while the share ages 65 and older increased from 17 percent to 20 percent. About 22 percent of the adult population is projected to be age 65 or older by 2020.

These shifts in the age distribution of the adult population have been accompanied by changes in the age distribution of householders. Between 2010 and 2017, the shares of householders under age 25, ages 25 to 44, and ages 45 to 64 all declined by 1 or 2 percentage points, while the share of householders ages 65 and older increased by nearly 4 percentage points. This increase in the share of older householders is contributing to growth in the shares of both married-couple households without children and one-person households. These trends are likely to continue as more baby boomers enter older age groups in the coming decades.

Fewer Young Adults Are Forming New Households

Young adults forming new, independent households—alone, with a spouse or partner, or with unrelated roommates—has historically been an important factor in the overall household growth rate. Between 2010 and 2017, the young adult population (ages 18 to 34) increased by 4.2 million, accounting for nearly a quarter of the growth in the adult population (ages 18 and older).10 Yet, the household growth rate slowed to only 3 percent during this period—much lower than the 11 percent growth rate between 2000 and 2010. While the living arrangements of adults ages 35 to 64 have remained stable, recent changes in young adults’ living arrangements help explain the decline.

The share of young adults ages 18 to 34 who have formed an independent household has declined since 2010, while the share living with their parents has increased sharply. In 2010, less than one-third (32 percent) of young adults ages 18 to 34 were living with their parent(s), but this share jumped to 35 percent by 2017. The increase was sharpest among 25- to 29-year-olds, rising from 21 percent in 2010 to 26 percent in 2017 (see Figure 2). The share of 30- to 34-year-olds living with their parent(s) also increased by 4 percentage points across this period. In contrast, the share of young adults living in a married-couple family declined for all age groups between 2010 and 2017, with the largest drop among those ages 25 to 29.

FIGURE 2. Share of Young Adults Living With Their Parents Increases, While Share Living With a Spouse Declines

article4-fig2@4x

Selected Living Arrangements of Young Adults Ages 18 to 34 (%), 2010 to 2017

Notes: “Other living arrangements” include householders living alone, with an unmarried partner, with other relatives, or with nonrelatives. Percentages may not sum to 100 due to rounding.
Source: U.S. Census Bureau, 2010 and 2017 American Community Survey PUMS.


The Great Recession and the slow economic recovery, high student debt loads, and high relative housing costs have all likely contributed to the declining shares of young adults forming or maintaining independent households since 2010. Whether these patterns persist into 2020 and beyond is an open question. If the job market and earnings continue to improve, the ability of young adults to form new households may increase. If housing costs continue to rise, however, the resulting economic burden on young adults may counteract any improvements in employment and earnings and dampen household growth rates in the future.


This article is excerpted from Mark Mather et al., “What the 2020 Census Will Tell Us About a Changing America,” Population Bulletin 74, no. 1 (2019).


 

References

  1. Frank Hobbs and Nicole Stoops, Demographic Trends in the 20th Century (2002), Figure 5-3; and U.S. Census Bureau, 2010 Census Summary File 1.
  2. Hobbs and Stoops, Demographic Trends in the 20th Century, Figure 5-2.
  3. U.S. Census Bureau, 2010 Census Summary File 1.
  4. U.S. Census Bureau, 2017 American Community Survey.
  5. Hobbs and Stoops, Demographic Trends in the 20th Century, Table 5.
  6. U.S. Census Bureau, “Table MS-2. Estimated Median Age at First Marriage, by Sex: 1890 to the Present,” www.census.gov/data/tables/time-series/demo/families/marital.html.
  7. Wendy D. Manning and Bart Sykes, Twenty-Five Years of Change in Cohabitation in the United States, 1987-2013, FP-15-01 (Bowling Green, OH: National Center for Family and Marriage Research, 2015); Larry L. Bumpass and James A. Sweet, “National Estimates of Cohabitation,” Demography 26, no. 4 (1989): 615-25.
  8. Joyce A. Martin et al., “Births: Final Data for 2017,” National Vital Statistics Reports 67, no 8 (2018).
  9. Wendy D. Manning, Susan L. Brown, and Bart Sykes, Trends in Birth to Single and Cohabiting Mothers, 1980-2013, FP-15-03 (Bowling Green, OH: National Center for Family and Marriage Research, 2015); and Joyce A. Martin et al., “Births: Final Data for 2017.”
  10. U.S. Census Bureau, Vintage 2017 Population Estimates.