The American Time Use Survey (ATUS) collects information on eldercare beyond what is observed directly in time diaries of ATUS respondents. From 2011-onward, information has been recorded on eldercare provision within the last three months for all ATUS respondents. Those who had provided care within the last three months gave additional information about the frequency of eldercare and their relationship with the recipient of the care. This blog post includes ATUS data from 2011-2024. 

Though the BLS defines eldercare recipients as being age 65 and older, in ATUS data, eldercare recipients can be younger. More than 98 percent of eldercare recipients in 2011-2024 ATUS data are age 50 and older, and more than 92 percent are age 60 and older. 

Women perform more family eldercare than men

Women bear the brunt of family eldercare, but gender gaps have shrunk over time. Between 2011 and 2024, 57 percent of family eldercare providers were women. The graph below (Figure 1) shows the share of men and women who provided eldercare to a family member by year. Each year, a larger share of women than men are eldercare providers within their families. Over the pooled time period, 15.6 percent of women provided eldercare to a family member, compared to 12.6 of men, meaning women were 23 percent more likely than men to provide family eldercare. 
 

The share of women who provide eldercare to a family member declined from 16 percent in 2011 to 14 percent in 2024. The share of men who provide eldercare to a family member also declined between 2011 and 2022, before increasing in 2023 and 2024. The simultaneous decline in women’s eldercare provision and the rise in men’s eldercare provision in the last two years of data have led to a near gender convergence in the rate at which U.S. adults provide eldercare to family members. 

Figure 1. Share of women and men that provide family eldercare over time

Women also provide family eldercare more frequently than men. The graph below (Figure 3) shows the percentage of male and female family eldercare providers who take care of their family member(s) daily; several times a week; about once a week; several times a month; once a month; or some other frequency that was not stated. Women are more likely than men to report providing care daily or several times a week. Women are less likely than men to report providing care at all lower frequencies.

Figure 2.  Frequency of family eldercaregiving by sex of caregiver

Caregivers are more likely to take care of women 

Family eldercare providers of both sexes are about twice as likely to care for a woman as they are to care for a man. The graph below (Figure 3) shows who male and female caregivers take care of in terms of the sex of the recipient family member(s). 

Slightly over half of family eldercare providers care for a woman (or women) only, shown by the pink bars. This is true for both male and female eldercare providers. Both men and women are much less likely to care for a man (or men) only than they are to care for a woman (or women) only. One in five male eldercare providers and 17 percent of female eldercare providers care for a man (or men) only, shown by the green bars. One in five male caregivers and one in four female caregivers care for at least one person of each sex, shown by the blue bars. 

This means that 80 percent of male caregivers and 83 percent of female caregivers take care of at least one female family member. In contrast, 40 percent of male caregivers and 43 percent of female caregivers take care of at least one male family member. In total, a family eldercare provider is roughly twice as likely to be caring for a woman as they are to be caring for a man.

These sex disparities in who family eldercare providers take care of could reflect differences in need for eldercare by sex (i.e., women may be more likely to need care), differences in receipt of needed care (i.e., men and women need care at the same rates but women are more likely to receive it), or differences in where older adults receive care (i.e., men and women are equally likely to need and to receive care, but women are more likely than men to receive it from family members).

Analytical consideration: While ATUS data on eldercare provision can tell us a lot about caregivers themselves, these data do not allow us to identify all older adults with met and unmet need for caregiving. This means it is not possible to determine—using ATUS data alone—which of the three scenarios described above is most accurate. ATUS data should be paired with other data sources to understand the need for eldercare and identify populations that are potential recipients of eldercare. Also note that when working with ATUS data on eldercare, weights are only available for the ATUS respondent themselves—that is, the caregiver. When weights are applied, ATUS respondents are representative of the U.S. population, but their care recipients are not necessarily representative. Therefore, analyses must be conducted at the level of the ATUS respondent—the caregiver—rather than at the level of the care recipient.

Figure 3. Sex of care recipient by sex of caregiver

Studies of eldercare and gender using IPUMS ATUS data

Forden, J. (2025). Elder caregiving frequency, labor force participation, and work. Journal of Aging & Social Policy, 37(5), 740-755.

Kim, S. O. (2025). Mobility of care and time poverty: the travel burdens of family caregivers in an aging America. Transportation, 1-23.

Radpour, S., Forden, J., & Ghilarducci, T. (2025). Unseen Costs: How Providing Eldercare Impacts Work and Economic Security. Generations, 49(3).

Reproduce these figures and analysis in Stata

Suggested citation

Pastoor, Isabel. 2026. “What ATUS Data Tells Us About Gender and Family Eldercare.” University of Minnesota Life Course Center, September 22, 2026. https://lcc.umn.edu/node/2161.

IPUMS Time Use consists of three data collections: IPUMS ATUS (American Time Use Survey), IPUMS AHTUS (American Heritage Time Use Study), and IPUMS MTUS (Multinational Time Use Study). Each of these data collections provides data from time diary studies, where respondents record their activities over a short period of time—usually a day—and include details about where and with whom they did the activity. IPUMS ATUS and IPUMS AHTUS provide U.S. data, while IPUMS MTUS provides data from 23 countries.

In IPUMS ATUS, time spent on community participation can be identified with the activity-level variable ACTIVITY—which codes each time use activity according to a detailed classification system—or with a number of person-level variables reporting the amount of time a respondent spent on various activities. Community participation can be captured in time spent on activities like volunteer activities, religious and spiritual activities (e.g., church services), attending events (e.g., sporting events, senior citizens meetings), and socializing (e.g., talking with friends). For each activity, users can identify with whom the respondent spent time, and where the activity took place. These variables can be used to determine, for example, how much time an older adult spent with others, or the types of places in the community older adults spend their time.

IPUMS AHTUS allows users to study time use in the U.S. for a limited range of years between 1930 and 2018. Information is available about the activity, who the respondent was with during the activity, and where the activity took place. The AHTUS data can be used to study trends in the community participation of older adults over a long range of time, albeit with less detail about the activities.

IPUMS MTUS provides time use data from many countries, allowing users to study community participation of older adults around the world and across time. Information is available about the activity, who the respondent was with during the activity, and where the activity took place. In some samples, more or less detailed information is available. Users should note that a number of samples only include respondents up to a maximum age.

In all three time use data collections from IPUMS, users can use our custom time use variable builder tools to measure older adults’ community participation. Custom time use variables report the amount of time spent on activities specified by the user, and can optionally include only time spent in certain locations and/or with certain people. For example, it is possible to create a variable that reports the amount of time each respondent spent out of their home and in the presence of at least one non-household member.

Users should consider pooling multiple samples together to ensure sample sizes are large enough to study a relatively small population (older adults) using time use data. Sample sizes can be found on the sample description page for each data collection.

Example studies of community participation using IPUMS data

• Chen, J. H. (2024). Pandemic and Older Adults’ Social Structure of Shared Time. The Journals of Gerontology: Series B, 79(2), gbad159.
• Yu, J., Huang, W., & Kahana, E. (2025). Temporal and Racial/Ethnic Patterns of Social Engagement among Older Adults: Evidence from American Time Use Survey 2019 to 2022. Journal of Applied Gerontology, 44(1), 116-125.

Suggested citation

Pastoor, Isabel. 2026. “Community Participation Among Older Adults: IPUMS Time Use Data.” University of Minnesota Life Course Center, August 25, 2026. https://lcc.umn.edu/node/2161.
 

Capturing Unpaid Caregiving for Older Adults

ATUS includes two complementary measures of adult caregiving. The first is activity-based, identifying respondents who report specific adult caregiving activities during the diary day. The second is survey-based, identifying respondents who regularly provide unpaid care to an adult who requires assistance. Using these measures either independently or in combination allows researchers to create a fuller picture of caregiving intensity, regularity, and overlap with paid employment or other ways of spending time (e.g., health behaviors, housework, leisure).

The ATUS also collects detailed information on labor market characteristics, such as occupation, wages, and hours worked, which allow researchers to connect caregiving behavior to engagement in the labor force. This linkage makes it possible to study associations between caregiving and employment, including reduced work hours or exits from the labor force—insights that are essential for designing family-friendly policies and supporting caregivers.

Analytical considerations

The ATUS is a one-day snapshot of time use for each individual respondent. Aggregated at the population level across the year, time diaries can be used to generate estimates of the average amount of time per day that respondents spent in adult caregiving activities in a given year. 

Researchers who are looking carefully at the data, however, may notice a disconnect for some ATUS respondents between the activities they report in their time diary (first measure of caregiving) and self-identifying as a caregiver (second measure of caregiving). This isn’t an error, but instead reflects reality for some caregivers. For example, a caregiver may share caregiving responsibilities for a parent with a sibling, dividing responsibilities by day. For the caregiver with Monday, Wednesday, Friday responsibilities who provides the activities they performed on a Tuesday, we might not observe any caregiving activities. This doesn’t mean the ATUS respondent isn’t a caregiver; rather they just weren’t surveyed about a day when they performed their typical caregiving activities. 

What this means for researchers using the ATUS to study caregiving is that they need to think carefully about who is in their sample and what this means for any conclusions they draw from their analyses. Be clear about defining terms and clearly describing who is and who is not in your analysis. 

Example studies using IPUMS data

Muench U, Jura M, Spetz J, Mathison R, Herrington C. Financial Vulnerability and Worker Well-Being: A Comparison of Long-Term Services and Supports Workers With Other Health Workers. Medical Care Research and Review. 2020;78(5):607-615. doi:10.1177/1077558720930131

Ulrike Muench, Joanne Spetz, Matthew Jura, Charlene Harrington, Racial Disparities in Financial Security, Work and Leisure Activities, and Quality of Life Among the Direct Care Workforce, The Gerontologist, Volume 61, Issue 6, September 2021, Pages 838–850, https://doi.org/10.1093/geront/gnaa190

Ahmed, T., Floro, M.S. Unpaid Care to Older Persons and Tradeoffs in Time Use: The Experience of Working-Age Women and Men in the US. J Fam Econ Iss 45, 71–87 (2024). https://doi.org/10.1007/s10834-023-09890-3

Wiersma Strauss, A. The earned income tax credit (EITC) and time spent helping and caring for adults. Rev Econ Household (2024). https://doi.org/10.1007/s11150-024-09731-8

Erin Ice, Bringing Family Demography Back In: A Life Course Approach to the Gender Gap in Caregiving in the United States, Social Forces, Volume 101, Issue 3, March 2023, Pages 1143–1170, https://doi.org/10.1093/sf/soac041

Citation: 

Introducing the Aging and Health Launchpad. (2026, May 18). Life Course Center, University of Minnesota. https://lcc.umn.edu/node/2011