Doctor talks to mixed race mother and child.

Family-Centered Care Matters for Kids With Special Needs, but Many Families Report Challenges With Providers

Families with limited resources or inconsistent insurance are more likely to face hurdles, new study finds.

Children and youth with special health care needs (CYSHCN) who receive family-centered care generally have better health outcomes, research shows. When health care providers engage and prioritize the needs of the family, CYSHCN enjoy better overall health; better access to coordinated, ongoing, comprehensive health care within a medical home; fewer emergency department visits; and fewer unmet health needs.

Yet in the United States, CYSHCN families from disadvantaged groups face barriers to receiving high-quality family-centered care, according to a new analysis of national survey data by Paul Morgan, now at the University at Albany, SUNY, and colleagues at Penn State University and SRI International.1

The researchers assessed family-centered care by measuring the extent to which doctors or other health providers:

  • Spent enough time with the child.
  • Listened carefully.
  • Showed sensitivity to the family’s values and customs.
  • Provided the family with specific information they need concerning the child.
  • Helped the family feel like a partner in the child’s care.

Data were from the 2016–2019 National Survey of Children’s Health (NSCH), which uses a five-question screener to identify CYSHCN.

The study focused on the quality of care received by CYSHCN families in visits to health professionals in the previous year and controlled for potentially confounding factors including children’s general health status and the severity of their impairments.

Socioeconomic Background Is Tied to the Quality of Family-Centered Care

Morgan and colleagues found that some CYSHCN families report greater barriers to receiving high-quality family-centered health care, including:

  • Families without consistent health insurance coverage.
  • Poor and lower-income families.
  • Single-parent families.
  • Families who usually receive care in a clinic or health center, emergency room, or other setting outside a doctor’s office.
  • Families of children with autism spectrum disorders, anxiety, or depression.

By contrast, families of CYSHCN with asthma—the most commonly reported special health care need—were significantly more likely to receive family-centered care than families of CYSHCN without asthma.

The results did not show consistent racial/ethnic disparities across all the measures of family-centered care—a finding that surprised the researchers. However, families of Black and Hispanic CYSHCN reported that providers spent relatively less time with their children compared with families of white CYSHCN. Families of Hispanic CYSHCN also said that providers showed less sensitivity to their family’s culture and customs.

A Targeted Approach Could Help Improve Care

Evidence from the study suggests that socioeconomic factors, rather than race or ethnicity, are central drivers of disparities in family-centered care among CYSHCN in the United States. To address these disparities, policies and systems of care serving these young people and their families can adopt comprehensive, coordinated approaches to increase provider-family engagement, cultural responsiveness, and shared decision-making, the authors noted.

To help particularly vulnerable CYSHCN families, targeted actions should focus on care provided in emergency departments, community clinics/health centers, and other non-office settings, and on providers caring for children with autism spectrum disorders or internalizing disorders, the authors suggested.


This article was produced under a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The work of researchers from Penn State University was highlighted.

 

References

  1. Paul L. Morgan et al., “Disparities in Family-Centered Care Among U.S. Children and Youth With Special Health Care Needs,” The Journal of Pediatrics 253 (2023): 297-303.e6.
01-24-Aging-Fact-Sheet-j

Fact Sheet: Aging in the United States

The current growth of the population ages 65 and older, driven by the large baby boom generation—those born between 1946 and 1964—is unprecedented in U.S. history.

This aging of the U.S. population has brought both challenges and opportunities to the economy, infrastructure, and institutions.

Demographic Shifts

The number of Americans ages 65 and older is projected to increase from 58 million in 2022 to 82 million by 2050 (a 47% increase), and the 65-and-older age group’s share of the total population is projected to rise from 17% to 23%.1

The U.S population is older today than it has ever been. Between 1980 and 2022, the median age of the population increased from 30.0 to 38.9, but one-third (17) of states in the country had a median age above 40 in 2022, with Maine (44.8) and New Hampshire (43.3) at the top of the list.2

The older population is becoming more racially and ethnically diverse. Between 2022 and 2050 the share of the older population that identifies as non-Hispanic white is projected to drop from 75% to 60%.3

The rising diversity among older Americans can’t match the rapidly changing racial/ethnic composition of those under age 18, creating a diversity gap between generations. In 2022, fewer than half of children ages 0 to 17 (49%) were non-Hispanic white.4 But research shows that there is fluidity in how people identify with racial/ethnic categories: Mixed-race Americans (particularly mixed Hispanic and white) increasingly see themselves as part of the white majority.5

Positive Developments

Education levels are increasing. Among people ages 65 and older in 1965, only 5% had completed four years of college or more. By 2023, this share had risen to 33%.6

Older adults are working longer. By 2022, 24% of men and about 15% of women ages 65 and older were in the labor force. These levels are projected to rise further by 2032, to 25% for men and 17% for women.7

The poverty rate for Americans ages 65 and older has dropped sharply during the past 50 years, from nearly 30% in 1966 to 10% today.8 The Census Bureau’s Supplemental Poverty Measure, which accounts for non-cash benefits, tax credits, and medical expenses, shows that 14% of older Americans lived in poverty in 2022.9

More older adults can meet their daily care needs. Older adults are functioning better on their own, and a shrinking share are living in nursing homes and assisted living settings than a decade ago. Home modifications and assistive devices such as walkers have helped older Americans maintain their independence.10

Challenges

Gains in life expectancy recently stalled. U.S. life expectancy at birth declined by 2.4 years between 2019 and 2021.11 The drop in life expectancy was driven largely by the COVID-19 pandemic, but deaths from drug overdoses, heart disease, chronic liver disease and cirrhosis, and suicide also played a role.12 Life expectancy rebounded slightly in 2022, to 77.5 years, but not enough to offset the decline during the pandemic.

Obesity prevalence among older Americans has increased at an alarming rate. In a single generation—between 1988-1994 and 2015-2018—the share of U.S. adults ages 65 and older with obesity nearly doubled, increasing from 22% to 40%.13

Wide economic disparities are found across different population subgroups. Among adults ages 65 and older, 17% and 18% of those identifying as Latino and African American, respectively, lived in poverty in 2022—more than twice the rate of those who identified as non-Hispanic white (8%).14

More older adults are divorced compared with previous generations. The share of divorced women ages 65 and older increased from 3% in 1980 to 15% in 2023, and for men from 4% to 12% during the same period.15

More older women are living alone. Over one-fourth (27%) of women ages 65 to 74 lived alone in 2023. This share jumped to 39% among women ages 75 to 84, and to 50% among women ages 85 and older.16

Older Americans face a caregiving gap, especially those with lower incomes and dementia.17 Demand for elder care is expected to increase sharply with a rise in the number of Americans living with Alzheimer’s disease, which could more than double by 2050 to 13 million, from 6 million today.18

Social Security and Medicare expenditures will increase from a combined 9.1% of gross domestic product in 2023 to 11.5% by 2035 because of the large share of older adults.19

Federal budget cuts and tax increases may be inevitable as more members of the large baby boom cohort reach retirement age and become eligible for entitlement programs. Policymakers can invest resources today to reduce poverty and improve the economic outlook for workers. These investments can increase young workers’ future productive capacity and help offset the costs of an aging population.

 


 

References

[1] U.S. Census Bureau, 2023 National Population Projections Tables: Main Series.

[2] U.S. Census Bureau, “America Is Getting Older,” June 22, 2023; and U.S. Census Bureau, 1980 Census of Population, Volume 1, Characteristics of the Population (PC80-1).

[3] U.S. Census Bureau, Projected Population by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2022 to 2100.

[4] U.S. Census Bureau, Projected Population by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2022 to 2100.

[5] Richard Alba, “What Majority-Minority Society? A Critical Analysis of the Census Bureau’s Projections of America’s Demographic Future,” Socius 4, no. 1 (2018).

[6] PRB analysis of data from the U.S. Census Bureau, Current Population Survey.

[7] U.S. Bureau of Labor Statistics, Civilian labor force by age, sex, race, and ethnicity, 2002, 2012, 2022, and projected 2032.

[8] Emily A. Schrider and John Creamer, “Poverty in the United States: 2022,” Table A-1. People in Poverty by Selected Characteristics: 2021 and 2022, Report no. P60-280, U.S. Census Bureau, Sept. 12, 2023.

[9] Schrider and Creamer, “Poverty in the United States: 2022,” Table B-2. Number and Percentage of People in Poverty Using the Supplemental Poverty Measure by Age, Race, and Hispanic Origin: 2009 to 2022, Report no. P60-280, U.S. Census Bureau, Sept. 12, 2023.

[10] Vicki A. Freedman, Jennifer C. Cornman, and Judith D. Kasper, National Health and Aging Trends Study: Trends Dashboards (2021).

[11] U.S. Centers for Disease Control and Prevention, “National Center for Health Statistics, Life Expectancy Increases, However Suicides Up in 2022,” Nov. 29, 2023.

[12] U.S. Centers for Disease Control and Prevention, “Life Expectancy in the U.S. Dropped for the Second Year in a Row in 2021,” Aug. 31, 2022.

[13] U.S. Centers for Disease Control and Prevention, National Center for Health Statistics, National Health and Nutrition Examination Survey.

[14] U.S. Census Bureau, Poverty Status of People by Age, Race, and Hispanic Origin: 1959 to 2022.

[15] PRB analysis of data from the U.S. Census Bureau, Current Population Survey.

[16] PRB analysis of data from the U.S. Census Bureau, Current Population Survey.

[17] Paola Scommegna and Morgan Sherburne, “Vulnerable Older Americans Aren’t Getting Adequate Care—Even With Paid Caregivers or Grown Children,” Population Reference Bureau, Oct. 19, 2022.

[18] Alzheimer’s Association. “2023 Alzheimer’s Disease Facts and Figures,” Alzheimer’s & Dementia 19, no. 4 (2023).

[19] Social Security Administration, Summary of the 2023 Annual Reports.

2022 PRB ANNUAL REPORT

Letter from the CEO

 

Informing a Smarter World / Shaping Change for Good

Navigating through Fiscal Year 2022 was an experience in responding to and shaping change: We successfully completed several long-time projects at Population Reference Bureau (PRB), expanded our operations in West Africa, broadened our areas of focus to include self-care and climate adaptation, and began developing a new strategic plan to guide us through the coming years.

Yet for all the change, some things remained constant: Every day, in every PRB office around the world—in Kenya, Senegal, and the United States—our staff continued to work intentionally to bolster people’s and organizations’ capacity to use population data in ways that will advance critical issues like equality, equity, and reproductive health.

For nearly 100 years, PRB has analyzed data, translated research, and shared information widely so it reaches audiences ranging from government officials to researchers, media, advocates, and the public. This work has made a difference in 2022: We developed a new definition of respectful care in reproductive, maternal, newborn, child, and adolescent health. U.S. policymakers are relying on our report about preserving and enhancing the American Community Survey. And our ongoing support to local partners’ research and communication priorities has led to our policy communication training program being embedded in the curricula of five research institutions and universities based in East and West Africa.

This FY22 annual report shares snapshots of some of our activities over the past year, who we worked with, and how our combined efforts came together to make a difference in people’s lives. The voices in this report show that, through all the changes we experience, it’s the relationships we build along the way that allow us to move forward, confident that our actions help ensure good data lead to good decisions that improve lives around the world.

 

Jeff Jordan, CEO and President

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PRB analyzes population data and ensures the research and its applications are understood and used widely by decisionmakers, advocates, and media. Our ability to both assess and easily communicate critical issues about topics like aging, gender equality, and sexual and reproductive health and rights makes us a valued partner and resource for those working at all levels and in all areas of the world, from the United States to Malawi to Bangladesh.

In 2022, we worked with new and long-time partners like the Appalachian Regional Commission, l’Ecole Supérieure de Journalisme des Métiers de l’Internet et de la Communication, Green Girls Platform, the MacArthur Foundation, the U.S. Census Bureau, and the Youth Alliance for Reproductive Health to communicate, convene, and share skills that get evidence-based information into the hands of decisionmakers in government, the private sector, and civil society who can put it to use creating positive change.

Key metrics from 2022: 560 persons or institutions strengthened with capacity-building activities, 137 information products published, 276 persons trained in policy communications, advocacy, or negotiation.

We believe that the most powerful solutions occur when we collaborate with and learn from one another.

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SHAPING CHANGE—TOGETHER—FOR GOOD

For decades, PRB has worked collaboratively with local organizations and partners so community members lead, set priorities, and identify solutions that are grounded in local realities. The work we do is often out of the spotlight.

The technical assistance and communications support we provide to data users, journalists, policymakers, youth advocates, and others in places like Appalachia, California, Democratic Republic of the Congo, Kenya, and Uganda doesn’t make us the center of attention—and that’s how we want it. As our Africa Director, Aïssata Fall, said about our work on the SAFE ENGAGE project, “We [try] to break the mold. It’s not about us having the funding, it’s about the principle and the commitment to partnership.”

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Empowering Evidence-Driven Advocacy (EEDA)

Bill & Melinda Gates Foundation

From 2017 to 2022, the EEDA project partnered with youth and civil society leaders working on family planning and sexual and reproductive health and rights in Africa and Asia. Together with these partners, EEDA developed tailored, data-driven advocacy strategies and communications materials to increase policy knowledge, strengthen commitment to implementation, increase funding for existing policies, and reinforce systems for promoting accountability. EEDA’s partners continue to make change happen in their communities.

Key metrics from the EEDA project: 111 tailored, targeted communication materials; 57 new family planning funding and policy commitments; 21 instances of strengthened implementation of existing policies; 17 organizations partnered with; 11 countries across Africa and Asia

“We had almost absolute discretion on how we would activate the information we got out of the analysis into advocacy strategies, and that work was driven by advocacy associates on the ground among their communities.”
—Ramya Jawahar Kudekallu, Project Director, International Youth Alliance for Family Planning
“For me, that’s why we’ve had so much success—because it was based on real evidence, carried out by real people in the states.”
—Madonna Badom, Advocacy Associate, Nigeria, International Youth Alliance for Family Planning

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Policy, Advocacy, and Communication Enhanced for Population and Reproductive Health (PACE)

United States Agency for International Development

For seven years, the PACE project worked together with local partners to build champions, bridge sectors, and distill evidence to ensure that family planning, reproductive health, and population issues are recognized as key to sustainable and equitable economic growth and development across Africa and Asia. The project ended in 2022, but its focus on connecting with local institutions and intentional shifting of program leadership to local partners ensures its aims and work continue.

Key results from the PACE project: 233 multisectoral policy dialogues; 242 positive changes to policies, strategies, and budgets; 646 media and news stories; 2,000 institutional and individual partners; 24 partner countries

“From the start of our partnership with PACE till now, we are treated as experts who bring much experience to the table and [are] trusted to lead programs with adequate and timely resources. We have played central roles in decision-making throughout…. This has resulted in BCAI’s exponential growth and expertise.”
—Sani Muhammad, Executive Director, Bridge Connect Africa Initiative (BCAI)
“[PACE] taught me how to use multimedia to advocate for issues on reproductive health and population and how to be concise and get the outcome required from policy advocacy campaigns.”
—Joy Munthali, Executive Director, Green Girls Platform, Malawi

A muslim woman wearing headphones and holding a microphone interviews a man sitting on the ground in

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Strengthening Evidence-Based Policy to Expand Access to Safe Abortion (SAFE ENGAGE)

Anonymous donor

For five years, the SAFE ENGAGE project created spaces for dialogue and collaboration among different stakeholders as they worked together to develop strategic messages aimed at improving access to safe abortion, strengthen the capacity of advocates to achieve policy goals, and work with journalists to improve evidence-based reporting. The project’s approach brought together partners from Anglophone and Francophone countries, creating connections that will endure long after the project’s end in FY22.

Key results from SAFE Engage: 102 spaces created for facilitating policy dialogue; 97 individuals trained and mentored in effective use of evidence for policy advocacy; 217 journalists trained in evidence-based reporting on abortion; 108 individuals trained in policy communications.

“As part of the SAFE ENGAGE project in Benin, we benefitted from a training workshop on political communication. During this workshop, we had the chance to meet with key players and decisionmakers in the safe abortion ecosystem in Bénin. It is obvious that the training has allowed us to network and create solid partnerships that will remain in the long term.”
—Béniel Agossou, Medical Students for Choice, Bénin

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In the United States, much of the policymaking around population health resides with states and localities. The decentralized nature of decision-making means that, to be effective, research and policy must focus on the communities they serve. PRB’s U.S. Programs staff provide trainings and resources to local leaders around the country to help them find the data they need on population, housing, and health trends so they can understand and respond to their communities’ needs.

In California, we are a force behind the scenes, working as an intermediary between data producers like the U.S. Census Bureau and the California Department of Education. We do the heavy lifting to make data and trends accessible across more than 1,000 indicators so that county program staff, journalists, advocates, and policymakers can spend their limited time and resources focusing on policy and program change instead of looking for the right data.

KidsData

Lucille Packard Foundation for Children’s Health, California Department of Public Health, and Donations from data users

The KidsData program promotes the health and well-being of children in California by providing an easy-to-use resource that offers high-quality, wide-ranging, local data to those who work on behalf of children in a way that is accessible to policymakers, service providers, grant seekers, media, parents, and others who influence children’s lives.

Key results from KidsData: 535 Indicators updated; 50+ new indicators to kidsdata.org; 144 indicators that came from the family experiences during the COVID-19 pandemic survey; 30 staff at the California Accountable Communities Health Initiative trained on using KidsData as a resource.

“KidsData is a great resource and I have used it many times. I appreciate how easy it is to disaggregate data by geographic and demographic groups. I also appreciate the analysis and context you have put together about the importance of certain issues. Thank you for maintaining this resource.”
—Anonymous attendee of the KidsData webinar on adverse childhood experiences, funded by the California Department of Public Health

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SHARING THE EVIDENCE

PRB information products in 2022 included blogs, briefs, fact sheets, reports, videos, and websites on topics like children’s well-being, family planning and reproductive health, equity, and the challenge of misinformation in today’s world. We’ve curated a sampling for you to explore.

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SUPPORTERS, PARTNERS, AND CONTRIBUTORS

We appreciate the organizations and individuals whose generous support makes our work possible. Thank you.

  • Annie E. Casey Foundation
  • Appalachian Regional Commission
  • Association of Monterey Bay Area Governments
  • Association of Public Data Users
  • Bill & Melinda Gates Foundation
  • California Department of Public Health Injury and Violence Prevention Branch
  • Consortium Regional pour la Recherche en Economie Générationnelle
  • Education Sub-Saharan Africa
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development
  • Foreign, Commonwealth & Development Office
  • Georgetown University-Institute for Reproductive Health
  • Hubert H. Humphrey Fellowship Program, Emory University, Rollins School of Public Health
  • John D. and Catherine T. MacArthur Foundation
  • Lucile Packard Foundation for Children’s Health
  • LVCT Health
  • Coordinating Center for the Centers on the Demography and Economics of Aging, University of Michigan
  • New Venture Fund
  • NORC at the University of Chicago
  • The Palladium Group
  • Population Council
  • San Benito Council of County Governments
  • The San Diego Association of Governments
  • Southern California Association of Governments
  • UnidosUS
  • United States Agency for International Development
  • United States Census Bureau
  • University of Utah
  • William and Flora Hewlett Foundation

PRB worked together with 48 organizations in 2022.

  • African Institute for Development Policy (AFIDEP)
  • African Population & Health Research Centre (APHRC)
  • Association des Journalistes et Communicateurs en Population et Developpement
  • Alliance Nationale des Jeunes pour la Santé de la Reproduction et la Planification Familiale (ANJSR/PF)
  • Amref Health Africa (Amref)
  • Association Burkinabé pour le Bien-Etre Familial (ABBEF)
  • Association des Gestionnaires pour le Développement (AGD)
  • Avenir Health
  • Break-Free From Plastic Initiative
  • Bridge Connect Africa Initiative (BCAI)
  • Cadres des Religieux pour la Santé et le Développement (CRSD)
  • College of Medicine, University of Ibadan
  • Community Safety Initiative Kenya (CSI Kenya)
  • Conseil pour la Défense Environnementale par la Légalité et la Traçabilité, en abrégé (CODELT)
  • Consortium Regional pour la Recherche en Economie Générationnelle (CREG)
  • Developing Radio Partners
  • Digital Data System for Development (DDSD)
  • Ecole Supérieure de Journalisme, des Métiers de l’internet et de la Communication (E-jicom)
  • EngenderHealth
  • Green Girls Platform
  • Innovations Environnement Développement en Afrique (IED Afrique)
  • Institut de Formation et de recherche Demographiques (IFORD)
  • Institut Supérieur des Sciences de la Population (ISSP)
  • International Youth Alliance for Family Planning (IYAFP)
  • Jimma University
  • JSI Research & Training Institute Inc. (JSI)
  • Kenya AIDS NGOs Consortium (KANCO)
  • Linda Arts Organization
  • National Center for Health Statistics (NCHS)
  • National Population Council Uganda (NPC Uganda)
  • Novel Association for Youth Advocacy (NAYA)
  • Open Development, LLC
  • Organization of African Youth
  • Palladium International, LLC (Palladium)
  • Philippine Business for Social Progress, Inc. (PBSP)
  • President and Fellows of Harvard College, Ariadne Labs (Ariadne Labs)
  • Reach A Hand Uganda (RAHU)
  • SERAC-Bangladesh
  • Solarkiosk Solutions GmbH (Solarkiosk)
  • The Medical Concierge Group (TMCG)
  • The Nature Conservancy
  • The Regents of the University of California, Berkeley Campus (UC Berkeley)
  • Visible Impact
  • World Relief
  • World Vision, Inc.
  • Youth Alliance for Reproductive Health-DRC (YARH-DRC)
  • YUWA
  • Zenysis Technologies (Zenysis)

Through their generous contributions, the individuals listed here allowed PRB to fund essential program expansion and organizational innovations during the fiscal year ending Sept. 30, 2022.

  • Jacob Adetunji
  • George Ainslie
  • Adrienne Allison
  • Amazon Smile Foundation
  • Nancy Andrews
  • Anonymous
  • Leslie Aun
  • Alaka Basu
  • Frederick L. Bein
  • The Benevity Community Impact Fund
  • Ulf Bergstrand
  • Sue Black
  • Nancy Bliss
  • Robyn Blumner
  • Doug Bradham
  • Bright Funds
  • Warren Y. Brockelman
  • Phyllis Burdette
  • William P. Butz
  • Dan Carrigan
  • James R. Carter
  • Julie Caswell
  • Alexandre Checchi
  • Joel Cohen
  • Cynthia Cook
  • Frances Craig
  • Robert Crosnoe
  • Xu Cui
  • Curtis Cummings
  • Geoffrey Dabelko
  • Philip Darney
  • Charles N. Darrah
  • Gouranga Dasvarma
  • Mark Davis
  • Ronald Dear
  • Viresh Desai
  • Carol DeVita
  • Thomas Dillon
  • Peter Donaldson
  • Marriner Eccles
  • Eldon Enger
  • Laurence L. Falk
  • Larry Feldpausch
  • David Finn
  • John J. Flynn
  • Neil Garrett
  • Armando Garsd
  • Campbell Gibson
  • Give Lively Foundation, Inc.
  • Amy S. Glenn
  • Linda W. Gordon
  • Bill Grams
  • Edward Guay
  • Kenneth Haddock
  • Stuart Harris
  • Marty Harte
  • William Hollingsworth
  • Pieter Hooimeijer
  • Richard Hope
  • Edwin W. and Janet G. House
  • Sherry F. Huber
  • Howard M. Iams
  • Robin Ikeda
  • Henry Imus
  • Eleanor Iselin
  • Amber Jackson
  • J. Timothy Johnson
  • Brad Jokisch
  • Jeffrey Jordan
  • Joan R. Kahn
  • Les Kanat
  • Robert B. Kelman
  • Lawrence Kintisch
  • Michael Kraft
  • William Kurtz
  • Willie B. Lamouse-Smith
  • Brian Larson
  • Thomas LeGrand
  • John Lindner
  • Melissa Lizarraga
  • Terri Ann Lowenthal
  • Andrew Lustig
  • David Lyons
  • Jennifer Madans
  • Liz Maguire
  • Nancy Matuszak
  • John F. May
  • Tom McCormack
  • Barbara McDade Gordon
  • Mary McEniry
  • Michael and Raina McManus
  • Norman Meadow
  • D.J. Mellema
  • Sara Melillo
  • Thomas W. Merrick
  • Frank Millard
  • Eugene Mulligan
  • Charles B. Nam
  • Network for Good
  • Margaret Neuse
  • Andy Neill
  • Elias Nigem
  • Lisa Palmer
  • Jeffrey Passel
  • Sandro Prudancio
  • David M. Radosevich
  • François Ramade
  • Michael Rengland
  • Teri Robers
  • Ian R.H. Rockett
  • Ricardo R. Rodriguiz
  • John and Libby Ross
  • James Rubenstein
  • Richard H. Sander
  • Andreas Schleicher
  • Elizabeth K. Schoenecker
  • Valdemar Schultz
  • Len Schwarts
  • Margaret Snowden
  • Jennifer Sciubba
  • Clifford Selby
  • Kyler Sherman-Wilkins
  • Rhonda Smith
  • Stanley Smith
  • Dick Solomon
  • Gary Steele
  • Lee and Byron Stookey
  • Bertram Strieb
  • Ram Subramaniam
  • Te Hsiung Sun
  • Calvin Gray Swicegood
  • Robert Tague
  • Chris Tarp
  • James W. Thompson
  • Robert L. Thompson
  • Clifford Treese
  • Katherine Trent
  • Joanna Umo-etuk
  • Anthony Vadala
  • J.W. Valentine
  • Noah Valloch
  • Pietronella Van Den Oever
  • Azucena Vicuña
  • Marianne Vigneault
  • Bonnie and Dirk Walters
  • George Weed
  • John Weeks
  • Jesse Wells
  • Michael White
  • Clarence J. Wurdock

FINANCIALS

Fiscal year ending Sept. 30, 2022

2022 PRB Financials

08-23-caregiving-in-europe-j

Off the Clock: Europeans Can Expect to Spend Over Half of Their Lives After Age 15 Providing Unpaid Care Work

Women spend more time as caregivers than men, and childless adults provide more support to their parents than those with children, studies on Europe show

Europe is the oldest region in the world, with almost one in five people ages 65 and older . Many European countries are concerned about the implications of this aging population, including a growing demand for old-age support and a shrinking pool of working-age people to provide it. As the urgency of the care-work crunch becomes more apparent, new research funded by the National Institute on Aging reveals that women and people without children take on a disproportionate share of this unpaid care work across the continent.

Europeans can expect to spend over half of their lives after age 15 providing unpaid family care work, including taking care of children and older relatives. However, women in Europe spend six more years doing unpaid caregiving work than European men, according to a study by Ariane Ophir, now at the Center d’Estudis Demogràfics, and Jessica Polos, now at DePaul University. 1

Ophir and Polos estimated care life expectancy, or the number of years after age 15 people can expect to spend providing informal care, by sex in 23 European countries. 2  Data on unpaid caregiving came from the European Social Survey , and life expectancy data came from the Human Mortality Database’s abridged period life tables.

FIGURE 1. Women in Europe Spend More Years Than Men Doing Unpaid Caregiving Work, but Patterns Differ Across Countries
Total care life expectancy at age 15 in years by sex, 2004/2005

Graph depicting the difference in total care life expectancy at age 15 between men and women in 23 European countries.

Source: Ariane Ophir and Jessica Polos, “Care Life Expectancy: Gender and Unpaid Work in the Context of Population Aging,” Population Research and Policy Review 41, no. 1 (2022): 197-227.

 

In the examined countries, the average care life expectancy is 33 years for men and 39 years for women, they found. And while the duration of caregiving life among men differs across countries—from 17 years in Portugal to 50 years in Norway—there is much less variability among women, reflecting how women consistently take on the primary caregiving burden, the authors explained.

By breaking down caregiving years by level of care, the authors also found that women spend significantly more time providing care at a high level, meaning daily or several times a week. In most of the examined countries, more than half of women’s caregiving years are spent on high-level care, compared to less than half of men’s. Women’s care life expectancy includes five to 10 more years of high-level caregiving than men’s in most countries, they found.

A similar gender gap in caregiving exists in the United States, according to Denys Dukhovnov of the University of California-Berkeley, Joan Ryan of the University of Pennsylvania, and Emilio Zagheni of the Max Planck Institute for Demographic Research.3 Compared to men who provide care, women spend 67% more time on average—around 50 minutes per day—providing unpaid care, their analysis found.

Using data from the American Time Use Survey and the Panel Study of Income Dynamics, Dukhovnov, Ryan, and Zagheni also showed that women in the United States spend twice as much time as men caring for young children, and that women in middle age spend slightly more time than men caring for older adults.

Both studies suggest the importance of considering the gender gap in informal caregiving when designing programs to promote more equitable work and family policies.

When counting unpaid family caregiving, older women and men in Europe can expect to work similar number of years

While women today are in the workforce longer than previous generations, they still spend fewer years employed than men in most European countries. But gender gaps in how long people work shrink or are even reversed when both paid and unpaid work are counted, a separate study by Ophir found.4

Ophir examined paid and unpaid working life expectancy at age 50 by sex, or the years 50-year-old women and men are expected to spend in employment and informal caregiving, including caring for grandchildren and helping older adults with daily activities. The study used data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) from 17 countries across Europe.5

Women’s working life expectancy is longer than men’s by up to a year in all but four countries, but the components of this work are very different for men and women, the study found. The largest component for women is years spent exclusively in unpaid work, while for men it is years spent only in paid work. Women are also expected to spend more years than men simultaneously in paid and unpaid work in most countries, compounding their caregiving burden.

Most of the years women and men care for grandchildren occur after retirement, while some of the years they spend caring for older adults happen while still employed, especially for men, the study found. While women spend more years than men providing both types of care, the gap is larger with grandchild care, possibly reflecting women’s tendency to retire earlier, Ophir says.

Though concerns over the care burden in aging societies often focus on caring for older adults, caring for grandchildren is also an important part of working life among older women, Ophir says. Debates on increasing retirement age and work-family policies should therefore incorporate an intergenerational perspective, she suggests.

The gendered pattern of caregiving years suggests that women’s “additional investment in unpaid care work in older adulthood, which conflicts with paid work and does not count toward pension benefits, could exacerbate gender inequality later in life and expose older women to additional economic disadvantages,” Ophir further explains.

Childless adults in Europe are more likely to support their older parents than adults with children

Luca Maria Pesando, now at New York University, found that adults with no children are about 20% to 40% more likely than those with children to provide financial, practical, and emotional support to their older parents, especially to mothers.6 Using Generations and Gender Survey (GGS) data from 11 European countries, his study examined support to older parents among adults ages 40 and older and whether having any children made a difference.7

Assessing the support provided to mothers and fathers separately also reveals gendered patterns. Women are more likely than men to provide support to mothers, regardless of whether they have children, Pesando found. Compared to those with children, both childless men and women are more likely to provide support to their mothers. In contrast, while childless women are more likely to provide support to their fathers, childlessness does not relate to the likelihood that men will provide support to their fathers.

The difference may reflect mothers being more socially and emotionally connected to their children than fathers, Pesando explains. Fathers are also more likely than mothers to have spouses still alive to provide support —reducing the potential burden on adult children—but the study controlled for this gender difference.

These findings are important in light of the growing share of childless adults in most European countries and concerns over the impact on demand for public support as people age. “These findings… support the view that researchers and policymakers should take into more consideration not only what childless people receive or need in old age, but also what they provide as middle-aged adults,” Pesando says.

Patterns of informal caregiving vary across countries, reflecting demographic and social characteristics

While most countries in Europe older populations compared to the rest of the world, life expectancy and fertility levels vary. Norms around gender and family responsibilities also vary, partly reflecting differences in social policies that affect gender equality and care provision. All three studies conducted in Europe show variations in their findings across countries, in part due to their unique demographic profiles, norms, and policies.

Ophir and colleagues show that while the care life expectancy does not vary substantially across countries, the proportion of years spent providing high-level care differs. In Nordic countries such as Denmark and Sweden, women and men have longer care life expectancies but spend a smaller share of this time providing high-level care; they also have smaller gender gaps in caregiving. These countries have more egalitarian gender ideologies than other European countries and more generous welfare regimes that include family caregiving, the researchers say. They are also similar across some demographic factors, such as total fertility rate, age at first birth, life expectancy, and healthy life expectancy, they note.

In countries in Southern Europe, such as Greece, and some Central and Eastern European countries, such as Slovakia, care life expectancies are shorter but involve greater shares of high-level caregiving. These countries rely more on families to take on primary caregiving responsibilities, the researchers note. They do not, however, share similar demographic profiles, suggesting the importance of social contexts in addition to demographic factors in shaping the nature of care life expectancy, they add.

In her analysis examining both unpaid and paid work, Ophir also finds variation across countries in the intensity of care. For example, while the overall working life expectancy is the longest for Swedish adults, most of their unpaid work was low intensity, reflecting the country’s generous welfare regime. While the overall working life expectancy is relatively shorter in Greece, Italy, and Poland, most of the unpaid work for women involves higher-level caregiving.

Pesando finds that adults are less likely to care for their older parents in Northern Europe, where comprehensive publicly funded programs can provide this care. Though differences are not large among countries in Eastern and Western Europe, adults are most likely to support older parents in Russia, followed by Czechia. Both countries are former socialist welfare states with heavy reliance on family support and limited publicly funded services for older adults, he notes.

Despite concerns over the economic implications of population aging and the labor force participation of older adults, informal caregiving has received little attention in policy debates. The disproportionate burden that falls on women and adults without children is therefore largely unnoticed. Discussions of aging-related policies, including pension reforms, old-age entitlements, and changes in the retirement age, should be informed by patterns in informal caregiving. Addressing informal caregiving also helps promote gender equality, especially in later life.

 

References and Notes

  1. Ariane Ophir and Jessica Polos, “ Care Life Expectancy: Gender and Unpaid Work in the Context of Population Aging ,”  Population Research and Policy Review  41, no. 1 (2022): 197-227.
  2. The 13 countries included in the study are Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Luxembourg, the Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, the United Kingdom, and Ukraine.
  3. Denys Dukhovnov, Joan M. Ryan, and Emilio Zagheni, “ The Impact of Demographic Change on Transfers of Care and Associated Well-Being ,”  Population Research and Policy Review  41, no. 6 (2022): 2419-46.
  4. Ariane Ophir, “ The Paid and Unpaid Working Life Expectancy at 50 in Europe ,”  The Journals of Gerontology: Series B  77, no. 4 (2022): 769-79.
  5. The 17 countries included in the study are Austria, Belgium, Croatia, Czech Republic, Denmark, Estonia, France, Germany, Greece, Italy, Luxemburg, Poland, Portugal, Slovenia, Spain, Sweden, and Switzerland.
  6. Luca Maria Pesando, “ Childlessness and Upward Intergenerational Support: Cross-National Evidence from 11 European Countries ,”  Aging & Society  39, no. 6 (2019): 1219-54.
  7. The 11 countries included in the study are Belgium, Bulgaria, Czech Republic, France, Georgia, Germany, Poland, Romania, Russia, the Netherlands, and Sweden.
08-23-southwest-b

Growth and Migration in the American Southwest: A Tale of Two States

5 takeaways from population data in Arizona and New Mexico

Having been on the forefront of Manifest Destiny, the Gold Rush, and post-World War II urban sprawl, the Southwest has had a long history of exponential growth, innovation, and development. But is this the case across the entire region?  

Here, we present a tale of two states—Arizona and New Mexico—and break down five reasons why the actual story is more nuanced than it seems. 

 

1. Their populations are not growing at the same rate. Compared to the nation as a whole, which grew by roughly 7% over the decade, New Mexico’s population growth was below average (3%), while Arizona’s was above average (12%). This difference is not explained by fertility rates in Arizona and New Mexico. Nor is it explained by mortality rates; despite New Mexico having a higher age-adjusted mortality rate than Arizona between 2010-2020, the difference is not impactful. It boils down to migration, especially of people moving from other, often neighboring, states. Heading into 2020, Arizona had a net migration gain of almost 600,000 new residents, while New Mexico had a net loss of about 40,000 people.

 

2. Metropolitan counties are booming, especially in Arizona. Growth in metropolitan counties drove population gains in Arizona and New Mexico from 2010 to 2020. And while most of the population in both states resides in metropolitan counties, the share is much higher in Arizona (Figure 1). This is partly due to the more urbanized landscape of the state: More than half of Arizona’s counties are classified as metropolitan, compared to less than 1 in 5 counties in New Mexico.  

Figure 1. 95% of Arizonans Live in Metropolitan Counties, Compared to 67% of New Mexico Residents
Percent of total state population, by county-type of residence

Sources: U.S. Census Bureau, 2020 Census Redistricting Data (Public Law 94-171); USDA Economic Research Service, 2013 Urban Influence Codes.

 

In fact, more people live in Arizona’s metro counties than in the entire state of New Mexico. The two largest counties in Arizona are each home to over 1 million people, while the largest in New Mexico has under 700,000. While Bernalillo County is home to 1 in 3 New Mexico residents, Arizona’s Maricopa County has over six times as many people (Figure 2).  

Figure 2. Across Both States, the Highest Population Concentration is in and Around Maricopa County, Arizona
Population density by county for Arizona and New Mexico, 2020

Source: U.S. Census Bureau, 2020 Census Redistricting Data (Public Law 94-171).

 

Migration into Maricopa County and surrounding counties has driven much of Arizona’s population growth. Meanwhile, most New Mexico counties saw negative net migration; 70% of the metro counties that grew experienced negative net migration, meaning the slight growth that they witnessed can largely be attributed to their birth and mortality ratios. Where New Mexico did see migration gains, the increase was likely due in part to job growth in the oil industry, which may not be sustainable over time.  

Figure 3. Maricopa County Accounts for the Large Majority of Migration Growth in the Area, With Net Migration More Than 6 Times the Next Highest County
Net migration in Arizona and New Mexico, by county, 2010-2019

Source: PRB U.S. Indicators: Net Migration (2010-19).

 

3. Metropolitan Arizona has an abundance of business and employment opportunities. Arizona boasts one of the fastest-growing economies in the country. Over the past half-decade, the state has consistently witnessed job, income, and sales growth above the national average, with Maricopa County experiencing significant expansions in sectors such as health care, information, construction, and accommodation and food services. Home to Phoenix and its multitude of edge cities, the county was the most populous and fastest-growing in the state from 2010 to 2020, witnessing a 16% jump in its population. New business and job growth, particularly in the tech industry, have earned the area the nickname “Silicon Desert”, reflecting its status as a prosperous, pro-business environment supportive of start-ups with a healthy job market that promotes in-migration but without the high cost of living of California’s Silicon Valley.  

 

4. New Mexico’s rural settings and struggling economic and education sectors are pushing people to leave. While New Mexico and Arizona rank similarly on quality of life indicators comparing cost-of-living, labor, inequality, life expectancy, and education characteristics, New Mexico lags a bit behind, mostly due to shorter life expectancy and lower rates of college degree attainment. Concerns about the quality of the K-12 education system may contribute to some of New Mexico’s out-migration, as families with children may choose to relocate to neighboring states for better schools. New Mexico scored among the 10 lowest ranking states on measures of fourth and eight-grade math and reading proficiency for the entirety of the 2010 to 2020 period.  

Differences in the states’ economic approaches and opportunities may also help explain the slow growth in New Mexico. While Arizona has largely focused on growing private markets and promoting entrepreneurship, New Mexico has concentrated more resources on public spending. While Arizona regularly ranked among the top 10 states for total job growth, New Mexico frequently ranked among the bottom 10 from 2010-2020. Low job growth combined with a lack of urban settings that appeal to young adults has resulted in out-migration of working-age people to surrounding states such as Arizona, Nevada, Oklahoma, and Texas in search of city life and better job opportunities.  

 

5. The future for the states presents different challenges. While job growth and the entrepreneurial spirit in Arizona may have their appeal, the state’s population growth is perpetuating increasingly urgent concerns about water availability amidst extensive residential development. Despite the current megadrought depleting the Colorado Riverthe primary source of water Arizona and all the states surrounding it—development continues without slowing. And while municipalities within Arizona are turning to other sources of water, such as groundwater and reservoirs, to continue accommodating population growth, these alternatives come with their own political complications and are finite. As the population grows and the water supply dwindles, Arizona is walking the limits on growth.

Meanwhile the out-migration of working-age adults and declining population of people under the age of 18 means New Mexico’s population is aging, which raises concern for further economic and quality of life consequences. Providing accommodations for a growing older adult population (such as healthcare, caregiving services, and accessibility modifications) and coping with a shrinking workforce puts pressure on the state’s economy. But recent trends, such as the rise in remote work, could present the opportunity to retain younger workers.  

08-23-b-young-adult-anxiety2

The Best Years of Their Lives? Young Adults Reported More Anxiety Than Older Adults During Pandemic, Despite Lower Health Risks

The anxiety age gap between young and older adults grew during the COVID-19 pandemic, PRB analysis finds.

Early adulthood is often thought of as an exciting time, marked by increased independence and new opportunities. As they enter their 20s, young people are often encouraged to enjoy the so-called best years of their lives. Yet, this stage can also be fraught with increased uncertainty and responsibility. especially for those navigating the transitions of young adulthood in a global pandemic, a new PRB analysis shows.

PRB analyzed data from spring 2020 through fall 2022 using the U.S. Census Bureau’s Household Pulse Survey to understand the anxiety of young adults (which we defined as people ages 18 to 29) relative to older adults (ages 60 and older). We found that more than 40% of young adults reported symptoms of anxiety—such as feeling nervous, anxious, or on edge—more days than not during the coronavirus pandemic.

These findings may not come as a surprise, given the events of the past three years: a global pandemic, record job losses during COVID-19 shutdowns, an attack on the U.S. Capitol, widespread demonstrations and global attention addressing systemic racism and police brutality, and the steepest year-over-year increase in consumer prices in 40 years.

What is surprising is that amidst these events, and despite facing greater health risks from COVID-19, older adults maintained much lower levels of anxiety than young adults during the pandemic. In fact, the anxiety age gap grew even as vaccines became available, restrictions were lifted, and the impacts of the pandemic on health, education, social relationships, and employment began to subside (Figure 1).

Figure 1. Young Adults Were the Most Anxious Group Throughout the COVID-19 Pandemic
Anxiety rates by age group, early and late pandemic period

Note: Early pandemic covers the period from April 23, 2020, to March 29, 2021, and late pandemic covers the period from April 27, 2022, to October 17, 2022. The Early Pandemic period reflects the period before vaccines were broadly available for COVID-19 while the Late Pandemic period reflects the period beginning one year after vaccine access began.

Source: PRB analysis of data from the U.S. Census Bureau’s Household Pulse Survey.

 

Here is what we know about the growing anxiety age gap during the COVID-19 pandemic:

1. Anxiety rates dropped more for older adults than young adultsthough young adults faced lower health risks.

Compared with young adults, older adults are much more likely to experience serious health issues from COVID-19 infections, and adults ages 65 to 74 have a COVID-19 death rate that is 60 times higher than the rate for young adults. Yet, as the pandemic progressed, the share of older adults reporting anxiety fell by 6 percentage points (from 22% to 16%), while anxiety rates for young adults decreased by 2 percentage points (from 43% to 41%).

 

2. Young adults were more anxious than older adults before the pandemic.

Recent cohorts of young adults have reported more clinical mental health symptoms than previous generations during the same life stage, a trend that extends back to the 1930s. Ahead of the pandemic, young adult anxiety was already rising, while older adult anxiety was on the decline.

Researchers have provided several explanations for this anxiety gap. Young adults may have different emotional responses to stressors than older adults, and older adults may be more likely to have received treatment for anxiety, resulting in fewer symptoms, or less likely to report their symptoms. Additionally, among young adults, addictive use of social media and growing concern about climate change and its impact on their futures have been linked to increased depression, anxiety, and stress among young adults.

 

3. The anxiety age gap grew for all racial and ethnic groups during the pandemic, but especially for Black adults.

The anxiety gap between Black young adults and Black older adults increased by 9 percentage points between April 2020 and October 2022. Black adults ages 18 to 29 saw a significant increase in anxiety (+3 percentage points), those 60 and older saw anxiety drop significantly (-7 percentage points).1

While the size of the gap grew most for Black adults, white non-Hispanic adults had the largest anxiety age gap overall at more than 25 percentage points. In fact, white young adults were significantly more anxious than their non-white peers, while white older adults were significantly less anxious than their non-white peers.

 

Figure 2. The Anxiety Age Gap Was Largest for White Adults, but Black Adults Saw the Gap Increase Most
Size of gap in anxiety rates by age group and racial/ethnic groups during the pandemic

Notes: Young adults refers to adults ages 18 to 29 while older adults refers to those ages 60 and older. Early pandemic covers the period from April 23, 2020, to March 29, 2021, and late pandemic covers the period from April 27, 2022, to October 17, 2022. The asterisk (*) in racial/ethnic categories denotes non-Hispanic.

Source: PRB analysis of data from the U.S. Census Bureau’s Household Pulse Survey.

 

4. Economic uncertainty alone does not explain the growing anxiety age gap.

Prior to the pandemic, many young adults were already worried about accessing and paying for health care, housing and food security, student loans, and personal debt. Young adults also have lower incomes, on average, compared with older adults—most of whom receive Social Security benefits. And they were particularly impacted by economic upheaval during the pandemic, especially those working in hospitality, leisure, and retail.  

However, using the Household Pulse Survey, we found that the share of young adults living in lower-income households (making less than $25,000 a year) decreased during the pandemic, dropping from 26% to 19% (Figure 3). Meanwhile, the share of older adults living in low-income households increased slightly.

While this may be partially explained by more young adults living with parents during the pandemic, we found similar patterns for job and housing insecurity; young adults’ economic well-being improved relative to older adults over the period examined, yet their anxiety rates did not fall in proportion to these improvements.

Figure 3. The Share of Young Adults Living in Lower-Income Households Declined During the COVID-19 Pandemic
Percent of persons living in lower-income households by age group and period

Note: Lower-income refers to persons living in households with incomes below $25,000. Early pandemic covers the period from April 23, 2020, to March 29, 2021, and Late pandemic covers the period from April 27, 2022, to October 17, 2022.

Source: PRB analysis of data from the U.S. Census Bureau’s Household Pulse Survey.

 

5. The pandemic uniquely affected areas of life young adults were already more worried about.

Because young adulthood is a period defined by personal, professional, and educational transitions, the pandemic’s impact on the economy, education systems, and opportunities for social interaction uniquely affected people in this age group. Pandemic conditions such as lockdowns, social distancing, shifts to virtual schooling, and restrictions on travel, intensified these areas of stress and worry that young adults were experiencing before the health crisis occurred.

Young adults were more likely to report that COVID-19 made it feel impossible for them to plan for their future, that their plans had been disrupted, and that their close relationships were negatively impacted. They were also more worried about issues unrelated to the pandemic that occurred during this period, including political elections, changes to abortion laws, rising suicide rates, and increased media reporting of sexual assault cases. Relative to older adults, more young adults report a desire to stay informed, but that following the news increased their stress and worry. While the relative health risks of the pandemic were lower for young adults, disruptions to the milestones associated with young adulthood made this age group particularly vulnerable to the mental health tolls of the pandemic. While recent media have emphasized the mental health crisis affecting teens, less has been reported about young adults’ psychological well-being.  More research is needed to determine the lasting impacts of pandemic disruptions on the mental health of those who entered and navigated the so-called best years of their lives during this period of global uncertainty.”

Note

1 Statistically significant at <0.0001.

 

Great Smoky Mountain Sunrise Over The City Of Gatlinburg Tennessee

Appalachia Makes Strides in Education and Economics, But Region Faces Enduring Challenges, New Data Shows

While a growing share of residents have college degrees, jobs, and rising incomes, Appalachia faces inequities in poverty, aging, and internet access compared to the rest of the United States.

A new report from PRB and the Appalachian Regional Commission (ARC) shows that Appalachia continues to improve in educational attainment, labor force participation, income levels, and poverty reduction. Drawing from the U.S. Census Bureau’s latest American Community Survey and comparable Census Population Estimates, The Appalachian Region: A Data Overview from the 2017-2021 American Community Survey, known as The Chartbook, contains more than 300,000 data points comparing Appalachia at the regional, subregional, state, and county levels with the rest of the nation. Key improvements include:

  • Median household income increased nearly 10% between 2012-2016 and 2017-2021, with 93 Appalachian counties experiencing 15% increases.
  • Bachelor’s degree attainment among people ages 25 and older increased by three percentage points to 26%, helping the Region surpass its milestone of more than one-quarter of residents attaining this level of education.
  • Appalachia’s labor force participation rates has risen slightly since the 2012-2016 period. Meanwhile, unemployment declined almost two percentage points—and even more in some parts of the Region.
  • Appalachia’s overall poverty rate (14.5%) decreased two percentage points between 2012-2016 and 2017-2021.
  • Southern Appalachia’s population increased more than 10% between mid-2010 and 2021, surpassing the average growth rate for the United States.

“The Chartbook clearly contains some good news for the Appalachian Region, with improvements on several measures of overall well-being,” notes Kelvin Pollard, senior demographer at PRB, who co-authored the report with PRB research analyst Sara Srygley and PRB senior fellow Linda A. Jacobsen. “At the same time, the data also tell us where vulnerabilities remain.”

Poverty, Aging, and Internet Access Issues Persist Across Region, With Some Counties Faring Worse

Despite the positive trends, several data points revealed vulnerabilities that underscore the inequities in Appalachia compared to the rest of the nation:

  • Though regional poverty rates declined overall, rates stayed the same or increased in 77 Appalachian counties.
  • A smaller share of Appalachian households had a broadband subscription compared to households in non-Appalachian areas. In 42 Appalachian counties, subscription rates were less than 70%. This gap in access, even within the Region itself, impacts residents’ ability to work remotely, participate in online learning, use telehealth services, and more.
  • Appalachia’s population trends older than the national average, with individuals ages 65 and older reaching at least 19.1% in 291 Appalachian counties. Additionally, the percentage of Appalachians ages 65 and older with a disability is more than three percentage points higher than the national rate.
  • The percentage of Appalachian households receiving payments from the federal Supplemental Nutrition Assistance Program (SNAP) was higher (over 13%) compared to all U.S. households (over 11%), with rates in Central Appalachia exceeding 20%. For households with children under age 18, Appalachia’s SNAP participation is higher than the national rate (21% and 18%, respectively).

“While Appalachia has improved on several key measures, data on broadband access and SNAP participation show that some conditions continue to be more challenging in the Region than in the rest of the country,” Srygley points out.

Rural Appalachia Lags Behind Region’s Urban Areas, Rest of Rural United States

The report also indicates that Appalachia’s rural areas continue to be more vulnerable than its urban areas. In addition, Appalachia’s 107 rural counties face unique challenges compared to 841 similarly designated rural counties across the rest of the United States. Specifically, rural Appalachia continues to lag behind the rest of rural America in educational attainment, broadband access, household income, and population growth.

In addition to the written report, ARC offers companion web pages on Appalachia’s population, employment, education, income and poverty, computer and broadband access, and rural Appalachian counties compared to other rural American counties. For more information, visit www.arc.gov/chartbook.

The Appalachian Region encompasses 206,000 square miles along the Appalachian Mountains from southern New York to northern Mississippi, including portions of 12 states and all of West Virginia.

The report uses data from the 2017-2021 American Community Survey and the Census Bureau’s vintage 2020 and 2021 population estimates—the most recent data available for the characteristics studied. It includes detailed tables and county-level maps covering state- and county-level data on population, age, race and ethnicity, housing occupancy and tenure, housing type, education, computer ownership and internet access, labor force participation, employment and unemployment, transportation and commuting, income and poverty, health insurance coverage, disability status, migration patterns, and veteran status. It also includes a detailed comparison of characteristics in rural Appalachian counties with those outside the Region.


About the Appalachian Regional Commission

The Appalachian Regional Commission is an economic development entity of the federal government and 13 state governments focusing on 423 counties across the Appalachian Region. ARC’s mission is to innovate, partner, and invest to build community capacity and strengthen economic growth in Appalachia to help the Region achieve socioeconomic parity with the nation.

USA, New Jersey, Jersey City, Boy (4-5) peeking through doorway

Public Housing, Vouchers Open Doors to Better Child Health, New Research Suggests

But common waitlist practices disadvantage families facing greatest hardships, analysis finds

Children in households that receive federal rental assistance are healthier and miss less school due to illness than those whose households are waiting for help, new research demonstrates.1

 

However, up to 75% of renters who need federal housing assistance—including public housing or rental vouchers—don’t receive it, data show. Most households that get assistance have incomes below the federal poverty line ($30,000 for a family of four in 2023) and a sizeable share live in deep poverty.2

Families receive rental assistance in three main forms:

  • Public housing units in buildings owned and run by local public housing agencies.
  • Vouchers that cover a portion of the cost for families to rent from a private owner.
  • Section 8 Project-Based Rental Assistance that subsidizes affordable units maintained by private owners.

But common waitlist processes for housing vouchers inadvertently favor more stable families, compounding the disadvantage for those facing the greatest hardships, another new study shows.3

Public housing buildings have been widely criticized for isolating disadvantaged families, and media have focused on disrepair. But for families struggling to pay rent and facing the threat of eviction, “receiving housing assistance is like winning the golden ticket,” says Andrew Fenelon, a sociologist and demographer at Penn State University.

Rental Assistance Tied to Better Child Health and Fewer Missed School Days

Children in households with rental assistance had fewer health problems and missed 22% fewer school days for illness compared with children whose households were waiting for assistance, Fenelon and colleagues found.

His research team examined the impact of rental assistance by comparing children in households receiving assistance with those in households that would receive it within two years. They used the National Health Interview Survey (NHIS), a nationally representative dataset, linked with administrative records on housing assistance from the U.S. Department of Housing and Urban Development (HUD) for 1999 to 2014.

Boy and the Houses

Children in households with rental assistance had fewer health problems and missed 22% fewer school days for illness compared with children whose households were waiting for assistance.

Fenelon suspects that the stability rental assistance offers families helps them better manage asthma—a major health reason children miss school. In an earlier study of NHIS and HUD data, Fenlon and colleagues found that children in households with rental assistance were less likely to go to the emergency room for a recent asthma attack than those in households awaiting assistance.4

Children in public housing tend to have more health problems than their peers who live elsewhere, including more frequent diarrhea, headaches, skin allergies, and asthma. But public housing does not make kids sicker, Fenelon found in another analysis of NHIS and HUD data.5

Investment in affordable and stable housing can boost school attendance by promoting better health, Fenelon says. Healthier kids do better in school and stay in school longer, creating long-term socioeconomic benefits, Fenelon argues.

“Disadvantaged families in public housing tend to have many challenges, but the inability to access stable and affordable housing is not one of them,” Fenelon says. With a reduced rent burden, families can invest more in their children, and with more stability they can better manage their children’s health care needs, he argues.

Rental Assistance May Create Lasting Health Benefits, Improve Child Behavior

In a separate study, receiving a housing voucher during childhood was strongly linked to lower hospitalization rates and less inpatient spending during young adulthood.6

Craig Evan Pollack of Johns Hopkins University and team analyzed data from the Moving to Opportunity (MTO) program, which tracked more than 4,600 families in five cities receiving either a traditional housing voucher, a voucher that could only be used in a low-poverty neighborhood, or no assistance between 1994 and 1998. Families in the two voucher groups lived in neighborhoods with similar poverty levels, and the program followed up with them 11 to 21 years later using hospital discharge and Medicaid data.

Looking at the reasons for hospital admissions, Pollack and colleagues found that children whose families received vouchers had significantly lower admission rates for asthma and mental health disorders compared to the control group.7 In contrast, there was no difference in emergency department use between the two groups.8 The findings suggest that housing policies that reduce childhood exposure to neighborhood poverty can reduce health care use into adulthood.

Another study using MTO data linked receiving a housing voucher to improved mental health among girls and fewer behavioral problems among boys when families moved to neighborhoods with less social disorder, Nicole M. Schmidt of the University of Minnesota and colleagues show.9 Social disorder was defined as public drinking, loitering, and police not coming when called.

By contrast, children were more likely to engage in delinquent behaviors in families that experienced housing hardship, reports Sarah Gold of Princeton University. Her findings are based on an analysis of the Future of Families and Child Wellbeing Study, which followed nearly 5,000 children born in large U.S. cities from 1998 to 2000.10

Housing hardship includes eviction, moving in with another household, homelessness, being unable to pay the rent or mortgage, and frequent moves. More severe or longer periods of housing hardship were associated with increased delinquent behavior such as vandalism, drug use, and assault. Delinquent behavior can lead to school suspension or expulsion, with lasting ramifications, Gold noted.

The link between housing hardship and delinquent behavior was the same for children in families with and without low incomes, suggesting that parental stress plays a role and that housing assistance may reduce stress.

“Children living in households with housing hardship may experience greater levels of family stress, which is linked to increased parental psychological stress and changes in parenting, which can lead to problematic behaviors in children,” writes Gold.

“Not only do children experience stress through their parents, but experiencing their own stress is linked to impulsivity, withdrawal, and aggression, all of which are associated with subsequent delinquent behavior,” she explains.

Woman and her daughter leaving home during COVID-19

The way housing voucher waitlists are managed unintentionally favors stability, disadvantaging families with the lowest incomes who move often.

Voucher Waitlists Disadvantage Families With Unstable Housing; Policy Changes Could Make a Difference

The way housing voucher waitlists are managed unintentionally favors stability, disadvantaging families with the lowest incomes who move often, Huiyun Kim of the University of Minnesota documents.11

Using administrative data and interviews with local housing authorities, Kim identified common practices that make it difficult for unstable families to compete for spots. These include giving preference to applicants who continue to live in the jurisdiction and purging applicants who do not respond to a mailing about their interest—often because they have moved.

Keeping shorter waitlists with more frequent openings, tracking applicants in multiple ways, and cooperating with neighboring jurisdictions could help level the playing field, Kim says.

Policy changes, including making more families eligible for housing assistance and increasing funding so more families can get help, would promote a more equitable system and lift more families out of poverty, he adds.

“By providing stable and affordable places to live, housing assistance deactivates an important way poverty is reproduced and reinforced,” Kim argues.

Stability, says Fenelon, is a key benefit that public housing offers struggling families.

Eviction can be devastating for families and children, Fenelon notes. Public housing authorities tend to have policies that protect tenants from evictions that private landlords who accept vouchers do not offer. Policymakers should consider ways to build the same stability into voucher programs, he says.

In addition, children in households with rental assistance often live in high-poverty neighborhoods, he reports. “Policymakers should consider the potential benefits to children and families of investing in parks, sidewalks, public transportation, libraries and other institutions in those neighborhoods.”


This article was produced under a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The work of researchers from the following NICHD-funded Population Dynamics Research Centers was highlighted: Pennsylvania State University, University of Minnesota, Princeton University, and Johns Hopkins University.

References

  1. Andrew Fenelon et al., “The Benefits of Rental Assistance for Children’s Health and School Attendance in the United States,” Demography 58, no. 4 (2021): 1171-95.
  2. Joint Center for Housing Studies of Harvard University, America’s Rental Housing, 2022, (Cambridge, MA: Joint Center for Housing Studies of Harvard University, 2022)
  3. Huiyun Kim, “Failing the Least Advantaged: An Unintended Consequence of Local Implementation of the Housing Choice Voucher Program,” Housing Policy Debate 32, no. 2 (2022): 369-85.
  4. Michel Boudreaux., et al., “Association of Childhood Asthma With Federal Rental Assistance,” JAMA Pediatrics 148 no. 6 (2021): 592-8.
  5. Andrew Fenelon, “Does Public Housing Increase the Risk of Child Health Problems? Evidence From Linked Survey-Administrative Data,” Housing Policy Debate 32, no. 3 (2022): 491-505.
  6. Craig Evan Pollack et al., “Association of Receipt of a Housing Voucher With Subsequent Hospital Utilization and Spending,” JAMA 322, no. 21 (2019): 2115-24.
  7. Craig Evan Pollack et al., “Using the Moving to Opportunity Experiment to Investigate the Long-Term Impact of Neighborhoods on Healthcare Use by Specific Clinical Conditions and Type of Service,” Housing Policy Debate (2021).
  8. Craig Evan Pollack et al., “Experiment to Decrease Neighborhood Poverty Had Limited Effects on Emergency Department Utilization,” Health Affairs 38, no. 9 (2019):1442-50.
  9. Nicole M. Schmidt et al., “Do Changes in Neighborhood Social Context Mediate the Effects of the Moving to Opportunity Experiment on Adolescent Mental Health?Health & Place 63 (2020): 102331.
  10. Sarah Gold, “Is Housing Hardship Associated With Increased Adolescent Delinquent Behaviors?Children and Youth Services Review 116 (2020): 105116.
  11. Huiyun Kim, “Failing the Least Advantaged.

Photo Credits

Header: Tetra Images

Photo 1: Steven Robinson Pictures

Photo 2: SDI Productions

Installation of solar panels on a roof.

Certain State Policies Are Linked to Better Health, Fewer Premature Deaths Among Working-Age Americans

Explore which state policies are tied to longer lives and fewer deaths from overdoses, alcohol abuse, and suicide

State policies are making a dramatic difference in how long working-age Americans live, contributing to the so-called deaths of despair from overdose, alcohol abuse, and suicide, new research shows.1

Over the 20-year span from 1999 to 2019, more conservative marijuana policies and more liberal policies on the environment, gun safety, labor rights, economic taxes, and tobacco taxes were tied to fewer premature deaths and better health among Americans ages 25 to 64, analysis by Jennifer Karas Montez at Syracuse University and colleagues shows (see Table).2

Table. State Policies Associated With Longer Life Expectancy, Fewer Deaths, and Better Overall Health Among Working-Age U.S. Adults
Types of State Policies Associated With Lower Mortality and Better Health Among U.S. Adults Ages 25 to 64, Between 1999 and 2019
Liberal Policies Strongly Related to Better Outcomes
Liberal Policies Related to Better Outcomes
No Correlation Between Policies Studied and Better Outcomes
Conservative Policies Strongly Related to Better Outcomes
Conservative Policies Related to Better Outcomes
N/A
Not Studied
Improved Life Expectancy
Lower Overall Working-Age Adult Mortality
Fewer Cardiovascular Disease Deaths
Fewer Alcohol-Induced Deaths
Fewer Suicides
Fewer Drug Poisoning Overdose Deaths
Better Overall Physical Health
Taxes
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
Liberal Policies Strongly Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
Liberal Policies Strongly Related to Better Outcomes
Fewer Alcohol-Induced Deaths
Liberal Policies Related to Better Outcomes
Fewer Suicides
Liberal Policies Related to Better Outcomes
Fewer Drug Poisoning Overdose Deaths
No Correlation Between Policies Studied and Better Outcomes
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Environment
Improved Life Expectancy
Liberal Policies Strongly Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
Liberal Policies Strongly Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
Liberal Policies Strongly Related to Better Outcomes
Fewer Alcohol-Induced Deaths
No Correlation Between Policies Studied and Better Outcomes
Fewer Suicides
No Correlation Between Policies Studied and Better Outcomes
Fewer Drug Poisoning Overdose Deaths
Liberal Policies Strongly Related to Better Outcomes
Better Overall Physical Health
Liberal Policies Strongly Related to Better Outcomes
Criminal Justice
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
Liberal Policies Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
Liberal Policies Related to Better Outcomes
Fewer Alcohol-Induced Deaths
Liberal Policies Related to Better Outcomes
Fewer Suicides
Liberal Policies Related to Better Outcomes
Fewer Drug Poisoning Overdose Deaths
Conservative Policies Related to Better Outcomes
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Gun Control
Improved Life Expectancy
Liberal Policies Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
Liberal Policies Strongly Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
Liberal Policies Strongly Related to Better Outcomes
Fewer Alcohol-Induced Deaths
Liberal Policies Strongly Related to Better Outcomes
Fewer Suicides
Liberal Policies Strongly Related to Better Outcomes
Fewer Drug Poisoning Overdose Deaths
No Correlation Between Policies Studied and Better Outcomes
Better Overall Physical Health
Liberal Policies Strongly Related to Better Outcomes
Health and Welfare
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
No Correlation Between Policies Studied and Better Outcomes
Fewer Cardiovascular Disease Deaths
No Correlation Between Policies Studied and Better Outcomes
Fewer Alcohol-Induced Deaths
No Correlation Between Policies Studied and Better Outcomes
Fewer Suicides
No Correlation Between Policies Studied and Better Outcomes
Fewer Drug Poisoning Overdose Deaths
No Correlation Between Policies Studied and Better Outcomes
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Labor (Private Sector)
Improved Life Expectancy
Liberal Policies Strongly Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
Liberal Policies Strongly Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
No Correlation Between Policies Studied and Better Outcomes
Fewer Alcohol-Induced Deaths
Liberal Policies Strongly Related to Better Outcomes
Fewer Suicides
Liberal Policies Related to Better Outcomes
Fewer Drug Poisoning Overdose Deaths
No Correlation Between Policies Studied and Better Outcomes
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Marijuana
Improved Life Expectancy
Conservative Policies Strongly Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
Conservative Policies Strongly Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
No Correlation Between Policies Studied and Better Outcomes
Fewer Alcohol-Induced Deaths
Conservative Policies Strongly Related to Better Outcomes
Fewer Suicides
Conservative Policies Strongly Related to Better Outcomes
Fewer Drug Poisoning Overdose Deaths
No Correlation Between Policies Studied and Better Outcomes
Better Overall Physical Health
Conservative Policies Related to Better Outcomes
Tobacco Taxes
Improved Life Expectancy
Liberal Policies Strongly Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
Liberal Policies Strongly Related to Better Outcomes
Fewer Cardiovascular Disease Deaths
Liberal Policies Strongly Related to Better Outcomes
Fewer Alcohol-Induced Deaths
No Correlation Between Policies Studied and Better Outcomes
Fewer Suicides
Liberal Policies Related to Better Outcomes
Fewer Drug Poisoning Overdose Deaths
No Correlation Between Policies Studied and Better Outcomes
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Immigration
Improved Life Expectancy
Liberal Policies Strongly Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Civil Rights and Liberties
Improved Life Expectancy
Liberal Policies Strongly Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
Liberal Policies Strongly Related to Better Outcomes
Abortion
Improved Life Expectancy
Liberal Policies Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Campaign Finance
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Education
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
LGBT Rights
Improved Life Expectancy
Liberal Policies Related to Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Labor (Public Sector)
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Voting
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes
Housing and Transportation
Improved Life Expectancy
No Correlation Between Policies Studied and Better Outcomes
Lower Overall Working-Age Adult Mortality
N/A
Fewer Cardiovascular Disease Deaths
N/A
Fewer Alcohol-Induced Deaths
N/A
Fewer Suicides
N/A
Fewer Drug Poisoning Overdose Deaths
N/A
Better Overall Physical Health
No Correlation Between Policies Studied and Better Outcomes

Source: Jennifer Karas Montez et al., “U.S. State Policies, Politics, and Life Expectancy,” The Milbank Quarterly 98, no. 3 (2020): 668-99; Jennifer Karas Montez et al., “U.S. State Policy Contexts and Mortality of Working-Age Adults,” PLOS One, 17, no. 10 (2022); Jacob M. Grumbach, “From Backwaters to Major Policymakers: Policy Polarization in the States, 1970-2014,” Perspectives on Politics 16, no. 2 (2018): 416-35; and Blakelee Kemp, Jacob M. Grumbach, and Jennifer Karas Montez, “State Policy Contexts and Physical Health Among Midlife Adults” Socius: Sociological Research for a Dynamic World 8 (2022): 1-14.

Note: A liberal policy was defined as expanding state power for economic regulation and redistribution or for protecting marginalized groups or restricting state power for punishing deviant social behavior; a conservative policy was defined as the opposite. For example, a high minimum wage would be categorized as a liberal policy, while low corporate taxes would be conservative.

 

Lack of State Investment in Residents Tied to Death Rate Increase

Death rates among working-age Americans increased 6% between 2010 and 2017. Meanwhile, death rates for infants and adults ages 65 and older fell and rates for children were unchanged, according to Montez. A spike in drug- and alcohol-related deaths and suicides during this period played a key role, she reports.

“The rise in deaths among Americans in the prime of their lives has been particularly alarming over the last decade. And it’s a major reason why overall life expectancy in the United States stopped increasing around 2010 and started to decline around 2014,” says Montez, who directs the Center for Aging and Policy Studies at Syracuse University.

“While some states have invested in their populations’ well-being—for example, raising the minimum wage, implementing an EITC [earned income tax credit], expanding Medicaid, enacting clean indoor air laws—other states have either not invested or even divested,” she says. “It’s this latter group of states where the lives of working-age adults are being cut particularly short.”

The research team analyzed data from 1999 to 2019. They combined mortality information from the National Vital Statistics System and annual data on 135 state-level policies scored on a liberal to conservative scale and grouped into policy domains including gun safety, the environment, labor, and tobacco.

The link between policies and mortality rates is straightforward in some cases, but less clear in others, the study authors caution.

Marijuana restrictions were the only conservative policies strongly associated with lower mortality, specifically from suicide and alcohol-related causes, the study found. According to Montez, marijuana can provide pain relief but has also been linked to an increased risk of developing problem drinking, depressive disorders, and schizophrenia, as well as a higher risk of motor vehicle accidents and suicide.

Overall, the study found that liberal policies in many domains were associated with lower mortality, Montez says.

“More firearm safety policies are strongly connected to men’s suicide risk, with more liberal policies predicting smaller suicide risk,” Montez says. “Tobacco taxes were linked to a lower risk of cardiovascular disease. Evidence shows they deter smoking.”

The U.S. Centers for Disease Control and Prevention report smoking causes one in four deaths from cardiovascular disease.3

Labor policies such as raising the minimum wage and mandating paid leave were strongly connected to fewer alcohol-induced causes of death and suicides among men, the analysis shows.

“Labor policies can help prevent economic hardship, allow workers to take time off when they are sick or need to care for loved ones without fear of losing their jobs or income, reduce stress, and prevent stress-related coping behaviors such as smoking and heavy alcohol consumption,” Montez adds.

“These findings provide new insights into which policy domains appear most important for health,” she says, “and they largely concur with existing evidence on the effects of specific policies on health.”

For example, the finding that policies in the labor domain are a strong predictor of working-age mortality concurs with other evidence that specific policies within that domain, like higher minimum wages and paid leave, reduce working-age mortality risk, she says.

The one discrepancy was the health and welfare policy domain, according to Montez. Although their analysis found that the domain was not associated with mortality, other evidence has shown that specific policies within that domain, like Medicaid, reduce mortality.

Policy Choices—Not Differences in the Characteristics of State Residents—Are Driving Lifespan Gaps

Death rates among working-age people have widened among states in recent decades, with the death rate nearly twice as high in West Virginia as in Minnesota. But these differences cannot be fully explained by the proportion of college-educated or higher-income residents or even by rising deaths of despair, Montez asserts.

“A major driver of these differences is policy choices,” she says. “Other scientists have reached a similar conclusion.”

She points to a study by Benjamin Couillard at the Federal Reserve Bank of Boston and colleagues who tested several explanations for the growing differences in working-age deaths between states.4

The research team documents that changes in states’ populations related to race, educational attainment, and income inequality have not played a major role in mortality patterns. Instead, they show that growing differences in working-age deaths between states are due to major shifts in state policies in recent decades.

“These [policy] decisions have had life and death consequences,” Montez says. 


This research was supported by the National Institute on Aging and conducted by a team of researchers including Jason Beckfield, Harvard University; Derek Chapman, Virginia Commonwealth University; Jacob M. Grumbach, University of Washington; Mark D. Hayward, University of Texas at Austin; Nader Mehri, Syracuse University; Shannon M. Monnat, Syracuse University; Steven H. Woolf, Virginia Commonwealth University; and Anna Zajacova, University of Western Ontario.

Christopher Munoz, Syracuse University, contributed to this report.

 


References

1Jennifer Karas Montez et al., “U.S. State Policy Contexts and Mortality of Working-Age Adults,” PLOS One, 17, no. 10 (2022).

4Montez et al., “Rising Geographic Disparities in US Mortality,” Journal of Economic Perspectives 35, no. 4 (2021): 123-46.

 

3D Emoji with Smiley Face

Happily Ever After? Research Offers Clues on What Shapes Happiness and Life Satisfaction after Age 65

Cognitive impairment and happiness are not mutually exclusive.

As Americans age, their happiness and life satisfaction tend to follow a U-shaped pattern, research shows. On average, people in the United States are happiest and most satisfied with their lives when they’re young, experience a decline in both metrics in their 40s (often called a midlife crisis), and then rebound in their 60s.

But what happens after age 65? Do spirits stay high in later life? How is happiness affected by events that happen as people age—like the onset of disabling health conditions or chronic pain, or the deaths of partners and friends?

Findings are mixed and researchers disagree; it depends on how, when, and to whom you ask these questions. “It’s a very heated area of study,” says Anthony Bardo of the University of Kentucky.

Research by Bardo and Scott Lynch of Duke University shows that the cognitive impairment than can accompany aging does not preclude happiness and a high quality of life. But other studies find that satisfaction with life and positive emotions decline with mobility problems and the deaths of spouses and other loved ones.

Despite puzzling society-wide patterns, research offers clues on how individuals might buffer their losses and buoy their spirits as they age, including staying involved in meaningful activities and maintaining a positive outlook. But more research is needed to confirm whether these actions can make and keep us happy or whether happy people are just more likely to do them.

Older People Report Happiness Despite Cognitive Impairment

Older adults can be happy and have a high quality of life despite experiencing some cognitive impairment, Bardo and Lynch show.1

They analyzed data for 1998 to 2014 from the nationally representative Health and Retirement Study. The study incorporated tests that examined participants’ ability to recall words and count backwards, among other tasks. It gauged happiness by asking whether respondents were happy all or most of the time or some or none of the time in the past week.

“This is a simple yet valid and reliable measure that is commonly used to assess how one feels about her or his overall quality of life,” Bardo says. If respondents needed a proxy to respond for them, the researchers categorized them as unhappy because the proxy version of the survey did not include questions about happiness.

On average, 65-year-olds can expect five out of 18 total years of remaining life to be lived with some cognitive impairment, the study found. Of those five years with cognitive impairment, the average person will live 4.4 years happy and about seven months (0.8 years) unhappy.

“Our findings show that happiness and cognitive impairment do coexist. Happy years of life were shown to substantially exceed the number of years one can expect to live with some cognitive impairment, on average,” Bardo reports.

The study’s main takeaway is that “even when cognitive impairment does occur, older adults can expect a large proportion of those remaining years to be happy ones,” Bardo says.

“People are frightened by the idea of dementia,” he points out. “Some cognitive decline is a normal process. Ideally, these findings will contribute toward reducing some of the stigma and fear.”

Programs that enable older adults with some cognitive decline to remain in their own homes, where most older people prefer to live, may add to their happiness and quality of life, Bardo suggests.

He also notes that we don’t yet know “how to assess the happiness or quality of life of someone with severe cognitive impairment. It’s an issue of great moral and ethical concern.”

Health Issues, Death of a Spouse Dampen Satisfaction With Life

Another study shows that health problems and losing spouses make people less satisfied with life as they age.

Péter Hudomiet, Michael D. Hurd, and Susann Rohwedder are RAND researchers affiliated with the National Bureau of Economic Research (NBER). They analyzed respondents’ reports of life satisfaction from the Health and Retirement Study from 2008 to 2016.2

“When we looked at cross-sectional data that captures a group of people at one point in time, then life satisfaction did indeed increase between ages 65 and 71 and hold steady thereafter, similar to earlier studies,” Rohwedder explains.

“But when we examined a group of individuals tracked over multiple years, we find their life satisfaction tends to fall as they age, and the rate of decline accelerates. Losing a spouse and deteriorating health play important roles in the growing dissatisfaction,” she adds.

Figure 1. Life Satisfaction After Age 65 Declines When Researchers Track the Same Group Over Time
Estimated Trajectories of Life Satisfaction Ascertained by Cross-Sectional and Longitudinal Methods

Source: Péter Hudomiet, Michael D. Hurd, and Susann Rohwedder, “The Age Profile of Life Satisfaction After Age 65 in the U.S.,” Journal of Economic Behavior & Organization 189 (2021): 431-42.

Note: The cross-sectional line shows average life satisfaction in the full sample. The longitudinal line is restricted to observations with valid reports in two adjacent survey waves; and the 2-year changes are tied together starting from the average level observed at age 65.

 

People with low life satisfaction die younger and thus make up a shrinking share of the older population, the researchers note—making drawing conclusions from data collected at a single point in time challenging.

“Mortality is substantially higher among those who tell interviewers that they are less satisfied with their lives compared to those who are more satisfied with their lives,” Rohwedder notes. “In addition, older people with physical or cognitive impairments are less likely to fill out a survey.”

The research team suggests their findings offer a more realistic perspective on the well-being and resilience of older people. “Without these findings, policymakers balancing the needs of the older population with those of the younger population may incorrectly conclude that older people are more satisfied with their lives than they really are and are of lesser concern,” Rohwedder explains.

Mobility Problems Take a Greater Toll on Well-Being Than Advancing Age

In later life, lower-body impairments may play a greater role than age in determining life satisfaction and emotional and physical well-being, a study led by Vicki Freedman at the University of Michigan finds.3

The research team challenges the notion of the U-shaped well-being curve—highest at youngest and oldest ages—by exploring multiple measures of well-being and considering the interplay of age and lower body limitations.

Their study analyzed 2013 disability and time-use data from the nationally representative Panel Study of Income Dynamics—a different data set than the Bardo and Lynch and NBER studies. These data, based on 1,600 adults ages 60 and older, include participants’ reporting of overall life satisfaction and their experienced well-being, or how they felt while doing certain tasks.

Life satisfaction was measured with the question, asked at one point in time, “Taking all things together, how satisfied are you with your life these days?” For well-being, respondents used daily diaries to record their emotions (happy, calm, frustrated, worried, or sad) and their pain and energy levels while doing randomly selected activities. They also reported lower body limitations—problems with hip, leg, knee, or foot movements.

The researchers found that overall life satisfaction was higher for individuals ages 65 to 74 than those ages 60 to 64, but they observed no age differences in the experienced well-being measures (mood, pain, and fatigue).

“What surprised us is that lower body limitations mattered much more than age in determining all three measures of well-being,” explains Freedman, “and this finding held across age groups.”

People ages 65 to 74 with mobility problems reported the highest pain and fatigue levels. According to Freedman, there may be an initial mismatch for people in this age range between activities and abilities (in other words, people overexert themselves), resulting in more pain and fatigue.

Research Offers Clues on Keeping Spirits High Despite Limitations and Losses

Older adults report they are happiest and most satisfied with their lives while socializing, working, volunteering, and exercising, a research team led by Jacqui Smith of the University of Michigan showed.4 Their 2014 study examined daily diaries of 4,600 participants in the Health and Retirement Study who recorded the amount of time they spent doing specific activities the previous day, the feelings they experienced, and the intensity of those feelings.

The researchers found that participants spent an average of 3.6 hours a day viewing television, an activity that some people experienced positively and others experienced extremely negatively. Television is passive, Smith notes, while activities that involve more social, mental, and physical engagement contribute the most to the positive side of adults’ daily emotional balance sheets, she says.

Finding ways to enable older people with disabilities to be involved in physical activity and volunteering could improve their well-being and satisfaction with their lives, Freedman argues. She points to research showing that older adults who make accommodations that allow them to carry out daily activities without assistance or difficulty—such as using a walker or taking public transportation instead of driving—report emotional well-being at levels close to those who don’t need accommodations.

Having adequate income may help some people adapt to their limitations, buffering the negative impact of impairment on their emotional well-being, another study led by Freedman shows.5

The loss of spouses and other family members presents different, more complicated challenges to happiness and life satisfaction. In Bardo’s view, humans tend to be resilient. He points to a body of research showing that as people reach older ages, they shed things in their lives that make them unhappy and accentuate the positive.

Bardo’s own research finds that as people move into their 70s and beyond, their family becomes a less important component of day-to-day happiness, and other aspects of life, such as health, friends and acquaintances, place of residence, and hobbies play a bigger role.6

This process of shifting focus and accentuating the positive “may largely explain why Americans, on average, become happier with age,” Bardo argues.

However, Rohwedder cautions that future research will need to confirm whether activities associated with greater life satisfaction and other measures of well-being actually cause this effect. “If the least happy die or drop out of the survey at greater rates, as our study documents, then individuals will appear happier at advanced ages, but they did not become happier.”

 


This article reflects research supported by the National Institute on Aging of the National Institutes of Health at the Centers on the Demography and Economics of Aging and Centers on the Demography and Economics of Alzheimer’s Disease/Alzheimer’s Disease and Related Dementias. Findings from researchers affiliated with the following centers are highlighted: Center for Population Health and Aging, Duke University; NBER Center for Aging and Health Research, National Bureau of Economic Research; and Michigan Center on the Demography of Aging, University of Michigan. Lindsey Piercy of the University of Kentucky contributed to this piece.

 

References

1. Anthony R. Bardo and Scott M. Lynch, “Cognitively Intact and Happy Life Expectancy in the United States,” The Journals of Gerontology: Series B, Psychological Sciences and Social Sciences 76, no. 2 (2021): 242-51.

2. Péter Hudomiet, Michael D. Hurd, and Susann Rohwedder, “The Age Profile of Life Satisfaction After Age 65 in the U.S.,” Journal of Economic Behavior & Organization 189 (2021): 431-42.

3. Vicki A. Freedman et al., “Aging, Mobility Impairments and Subjective Wellbeing,” Disability and Health Journal 10, no. 4 (2017): 525-31.

4. Jacqui Smith et al., “Snapshots of Mixtures of Affective Experiences in a Day: Findings From the Health and Retirement Study,” Population Ageing 7, no. 1 (2014): 55-79.

5. Vicki A. Freedman et al., “Late Life Disability and Experienced Wellbeing: Are Economic Resources a Buffer?” Disability and Health Journal 12, no. 3 (2019): 481-8.

6. Anthony R. Bardo, “A Life Course Model for a Domains-of-Life Approach to Happiness: Evidence from the United States,” Advances in Life Course Research 33 (2017): 11-22.