IPUMS ATUS

Community Participation Among Older Adults: IPUMS Time Use Data

Community participation and social interaction are important determinants and expressions of health and wellbeing, particularly for older adults, who are more likely to live alone than younger people. Time use data is an excellent source of information on community participation among older adults. This blog post showcases the opportunities for studying community participation among older adults using IPUMS Time Use data.

Older adults doing ballet in a community class

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

Author

Isabel Pastoor

Date

2026-08-25

Understanding the Paid Care Workforce

Paid care work forms the backbone of the U.S. health and social care systems, encompassing a wide range of occupations responsible for delivering clinical care, personal assistance, and preventive services. Despite its central role in population health and economic functioning, paid care work remains challenging to measure systematically. Care jobs are often distributed across diverse settings, span multiple occupational classifications, and involve complex combinations of clinical, relational, and administrative tasks that are not always well captured in traditional labor statistics. As a result, researchers require data infrastructure that links detailed employment information with demographic and contextual characteristics to fully understand the paid care workforce

Paid care worker at a table with an elderly person

IPUMS provides harmonized data from major national surveys that make it possible to study paid care work consistently across time and across data sources. Drawing on datasets such as the American Community Survey and the Current Population Survey, IPUMS enables researchers to identify paid care workers using detailed occupation and industry codes and to analyze their wages, hours, job stability, and demographic characteristics. By supporting longitudinal and cross-sectional analyses, IPUMS allows researchers to examine employment trends, workforce composition, and inequality within the paid care sector.

Measuring Paid Care Work

Paid care workers can be identified in datasets like the American Community Survey (ACS) and the Current Population Survey (CPS), available through IPUMS USA and IPUMS CPS. These datasets include detailed occupation codes, which are based on the Standard Occupational Classification (SOC) system, which allow researchers to examine groups such as nursing assistants, personal care aides, home health workers, and community health educators. Industry codes, which are based on the North American Industry Classification System (NAICS), allow researchers to identify the setting in which an individual is working, such as a hospital, a physician’s office, or a home-based setting.

By limiting one’s data file to individuals with a specific set of occupation and/or industry codes and drawing on wage, hours worked, and demographic information, researchers can analyze important dimensions of the healthcare workforce such as job quality, employment trends, and disparities across race, gender, and geography. Because the data are harmonized across time, users can trace how care work has evolved in response to demographic shifts, policy changes, and public health crises.

Analytical considerations

Change over time. An important consideration in measuring paid care work is that occupation and industry codes are revised and change over time. They are revised appropriately every ten years due to changes in the types of work that are performed and to enumerate new and emerging occupations. Consequently, to measure occupation and industry over time, researchers either need to standardize occupation codes using crosswalks or use a standardized occupation variable provided by IPUMS.

Measuring turnover and employment transitions. A question that a lot of researchers, practitioners,and policy makers want to know about paid care workers is how many, or what percent, of workers are leaving their jobs, how many are entering, and how many are changing industries or occupations. Good news! IPUMS CPS includes a harmonized longitudinal panel that allows researchers to track individuals over a 16 month period. When selected into the CPS sample, household members are surveyed in four consecutive months, left un-enumerated during the subsequent eight months, and then resurveyed in each of another four consecutive months. New rotation groups are brought into the CPS sample each month. An employment transition can be identified when an individual was employed as a paid care worker in the prior month and then reports working in a new occupation in the subsequent month.

Choosing the right dataset. Choosing the right IPUMS dataset to measure paid care workers depends on your research question. IPUMS USA, which includes the American Community Survey, has the largest sample sizes and best representation of workers across occupation, industry, and other factors, including geography, The IPUMS CPS has a smaller sample size, but the longitudinal panel within the CPS allows workers to better measure employment transitions or turnover (described above). Finally, the CPS March Supplement, called the Annual Social and Economic Survey (ASEC), provides more contextual data for researchers, including jobs and income held in the last year and other work characteristics, like health insurance.

Example studies using IPUMS data

Azaroff LS, Woolhandler S, Touw S, Bor D, Himmelstein DU. Deporting Immigrants May Further Shrink the Health Care Workforce. JAMA. 2025;333(22):2018–2020. doi:10.1001/jama.2025.3544

Baughman RA, Stanley B, Smith KE. Second job holding among direct care workers and nurses: implications for COVID-19 transmission in long-term care. Medical Care Research and Review. 2022 Feb;79(1):151-60. https://doi.org/10.1177/1077558720974129

Dill JS, Frogner BK. The gender wage gap among health care workers across educational and occupational groups. Health Affairs Scholar. 2024 Jan;2(1):qxad090. https://doi.org/10.1093/haschl/qxad090