Social epidemiology and time use

Abstract

Examining disease progression and associated risk and protective factors over time is essential for epidemiology. “Over time” can be understood as discrete events in people's lives that affect their health outcomes, including exposures and behaviors. For social epidemiology, this is of interest because time spent in social situations is required to benefit from those interactions. A wide range of social relationship types has been linked to health outcomes. Social relationships take time to develop and include spending time with others. Spending time with others has been shown to lead people to adopt beliefs, priorities, and behaviors from the group. Therefore time with others influences decisions about how to spend time and, potentially, health trajectory. More research is needed on how time affects the relationships between social influence and health. This commentary explores gaps in the social epidemiology field related to time use and suggests ways to address these gaps through data collection and analyses.

Keywords

economic decision-making methodology social epidemiology social norms social relationships social structure time use

Introduction

Time is a central variable in disease risk and progress at the individual and community levels. Infectious diseases often require a minimum time of exposure for enough virus to enter the body, and chronic diseases require a certain amount of time to develop into a clinical condition. Each of these trajectories includes discrete daily events that are often under-examined in epidemiology. Time use measurement is limited in public health although daily time use is implicit in many health behaviors and predictor and outcome variables. The concept of measuring disease “over time” is foundational to epidemiology, but generally different from daily time use. Although daily time use is a composite element of longer-term time assessments, more finite and specific measures can be used to identify discrete actions that make up disease progression “over time.”

As two primary introductory notes, time may be perceived or marked in different ways. This commentary provides a general discussion without specific mention of how time is marked, measured, or understood by different people. Additionally, this commentary will be referring primarily to commercial time, marked by 24-h day, divided into hours. It will not refer to other metrics of time, such as solar time or perceived time. Second, the current commentary will focus on adults who have more agency over how they spend their time, except where explicitly identified. Understanding time use among other populations, such as children and minor adolescents, clinical populations, and institutionalized adults, will require different methods because of the degree to which other people or external forces limit their agency regarding how members of these groups spend their time.

Social determinants of health affect a wide range of protective and risk factors (NEJM Catalyst, 2017). Social relationships are a key social determinant that requires spending time with other people. Positive and important relationships in people's lives often take the most time to develop. However, this is not highlighted directly and measured in detail in most social epidemiology studies. The purpose of this commentary is to identify ways that time use has been measured and used in the past, gaps based on current evidence and theory, and ways to improve the measurement of time use and social relationships to identify intervention points.

This commentary follows the conceptual model illustrated in Figure 1, in which structural factors affect individual decision-making about what to do with daily time. The commentary discusses how those decisions are linked to health status specifically through time spent in social relationships, which have been shown to have protective health effects.

Figure 1.

Conceptual model.

Current common uses

Time-use studies start from the obvious assumption that each day has a finite amount of time. People spend time on necessary activities, such as eating and sleeping, along with other essential activities for maintaining a healthy life, such as working, child care, and associated transportation (e.g. commuting). Along with these activities, public health professionals recommend many preventive health behaviors, which take time in people's daily lives. Starting with the most common topics that have a time element, research has shown that minimum levels of sleep are beneficial for maintaining physical and mental health (Alvarez and Ayas, 2004; Dong et al., 2022; Glozier et al., 2010; Hirshkowitz et al., 2015; St-Onge et al., 2016). These studies often indicate 7–8 h of daily sleep per day for adults, and more hours at earlier developmental stages. Additionally, including 2 h and 30 min (150 min) of moderate to vigorous physical activity per week has been shown to reduce the risk of many adverse health conditions (Piercy et al., 2018; World Health Organization, 2019).

Little research has been done to assess the burden of spending time on healthy behaviors. For example, nutrition recommendations dictate eating a variety of foods that include vegetables, fruits, and lean protein (Institute of Medicine Food Nutrition Board Committee on Dietary Guidelines Implementation, 1991). However, eating healthy in these ways often involves preparing those ingredients, either for each meal or some other interval (e.g. weekly). Another example is preventive clinical service utilization. Accessing health and social services can help people improve their physical and mental health. However, social, policy, and economic barriers often reduce the accessibility of these services (Lowery, 2021).

Additional studies in the fields of economics and social sciences have detailed accounting of daily activities for participants, but focus on economic activities and productivity levels, and often omit important information for understanding public health implications. For example, many surveys combine all “out-of-home leisure” or other similar non-paid or non-market value activities into broad time-use categories (Budlender, 2007; Charmes, 2015; Gershuny, 2011). These categories do not account for discrete activities or how those activities may be beneficial or detrimental to the health status of the participant, even when analyzing them in association with well-being (Gershuny, 2011). Prior studies have tracked time spent with others, but with minimal detail about the nature of those relationships, which is important for understanding the social effects on public health (e.g. closeness of others involved, content of activities, feelings associated with that time in social activity) (Charmes, 2015).

More information is needed on the tradeoffs between time spent working for financial return and completing household work and errands versus time spent in leisure activities, including social activities. These challenges are summarized in a study of how adolescents manage multiple domains of activities. Authors note that time spent pursuing one type of activity is necessarily at the expense of any other type of activity (Shanahan and Flaherty, 2001). This is an important consideration in making decisions about how to spend time. People may not engage in social activities that lead to positive health outcomes if they are working or engaged in other related activities (e.g. commuting, shopping for work, etc.) (Charmes, 2015). While work can facilitate social relationships that may carry on outside of work hours, working hours may still limit the time available for social activities. Additionally, studies of time spent on household chores, and the gender differences in these activities (Kan and Kolpashnikova, 2021; Kolpashnikova and Kan, 2021) have found that those who identify as female, are doing both paid and unpaid work, leaving little time to develop long-term social relationships.

Spending time with others can be beneficial for physical and mental health (Friedman et al., 2024; Holt-Lunstad, 2022; Holt-Lunstad et al., 2010; Leigh-Hunt et al., 2017). However, developing the types of social relationships that have a positive impact on health status takes time, both in terms of discrete events and over the lifespan. Literature discussing this is lacking. Available data focus on time spent engaging in social activities (e.g. the American Time Use Survey [ATUS]) and self-reported relationship intensity. Existing data do not indicate transitions in the nature of relationships (e.g. break-ups, losing contact with those once important, increasing intimacy, and important life events).

Despite research showing social connectedness as a protective health factor, recent studies show that people are spending more time on their own. Several researchers have documented declining participation in formal social groups over the past three decades (Kannan and Veazie, 2023; Putnam, 2000). While this trend may be attributed partially to the effects of COVID and physical distancing guidelines, a significant portion may be attributed to isolating economic structural factors (Bindamnan, 2023; Øversveen, 2022; Shade, 2021).

The decline in the value of wages relative to inflation is associated with a need to spend more time working, potentially at multiple jobs (Auray et al., 2018; Mishel et al., 2015; U.S. Bureau of Labor Statistics, 2024), and, therefore, less time socializing (Kannan and Veazie, 2023). Low-wage jobs also include strict time restrictions (e.g. time spent per delivery for drivers, time spent per item for warehouse fulfillment workers, etc.) and variable schedules, which can increase stress and risk of injury, and decrease life satisfaction (Cheung and Lucas, 2015; De Castro et al., 2010; Laske et al., 2022; Lee et al., 2020; Park et al., 2018; Thomson et al., 2022).

Research has consistently found that people with higher socioeconomic status (SES) have more social support (Ajrouch et al., 2001; Schafer and Vargas, 2016; Weyers et al., 2008). This may be attributed in part to needing to spend less time working and having more leisure time to join organizations or social groups.

Time, social relationships, and structural factors

Understanding demands on people's time can illuminate an important pathway to understanding how socioeconomic position affects decisions regarding how to spend time. Commonly, people prioritize their primary means of economic security (their job), compared to family and childcare time, and leisure, and other social activities (Kannan and Veazie, 2023). Collecting data on these priorities along with daily time use can potentially link individual daily life to structural factors affecting public health. In short, social structures include economic systems which are the rules and procedures of creating and allocating resources and services, the institutions charged with maintaining those systems, and social structures, which are the norms and perceptions of what are acceptable ways to act that derive from those systems and institutions (Marx, 1867, 2004).

In the current economic system, labor is divided among specialized activities. This division of labor means that people do different work that have different public health outcomes as a result of varying levels of workplace safety, health outcomes associated with work activities, workplace culture, and relationships with coworkers. Analyses of time expenditure should assess the nature of work activities. For example, office workers may have less physically strenuous or dangerous jobs and may have fewer adverse workplace exposures than people whose jobs require strenuous activity. They may have more free time for preventive health behaviors and positive social relationships. However, they may have a higher risk of mental health issues due to the lack of physical activity and potential isolation from colleagues.

Often individual decisions are informed by higher-level influences such as social group norms about what is acceptable behaviors and macroeconomic and political circumstances (Bicchieri et al., 2023; UNICEF, 2021). Social norms include prioritization of work or interest in certain social or leisure activities that could be protective or risk factors for adverse health conditions. Tracking individual time use on a finite and daily level along with data about people's social, economic, and political circumstances serves to link individual outcomes to structural factors.

Space-time geography frameworks present key considerations about time use, social relationships, and epidemiology. Space-time geography research acknowledges that people occupy a space for an amount of time, and conduct daily activities, such as work, in that space. The space people occupy and the amount of time they spend there is socially ordered (Kwan, 2013; Rainham et al., 2010). Social structures govern where people live and work, whether and how people travel, and the exposures (both environmental and social) they experience in those spaces. Additionally, work in this field assesses how illnesses that limit people's ability to go to certain spaces necessary to complete their daily activities disrupt processes that determine where and how people spend their time (McQuoid et al., 2015, 2017).

Space-time geography studies use methods that identify where people are for an amount of time. Similar methods could be used to assess how length of time in social interactions after the degree to which these interactions and relationships are protective health factors. Social structures have important implications for how much time people have for social relationships, and principles from space-time geography provide a methodological foundation for future studies of social epidemiology and time use.

Relation to embodiment

An essential element of the Ecosocial Theory of Disease Distribution (Ecosocial Theory) is that a person's body and health status represent the impact of their experiences and behaviors (Krieger, 2005, 2011, 2021). Time is an inherent part of this assertion. Daily time use is the pathway through which long-term exposures develop, both environmental and behavioral or social. The contexts identified in the Ecosocial Theory as being an essential part of understanding health include economic, political, environmental, and social elements. For example, driving past a dry cleaner shop is much different from living above one, and living above a dry cleaner shop and spending all your time in the apartment is different from living above a dry cleaner shop and spending hardly any time at home.

A brief emphasizing on this concept is important because it conceptually links the structural factors discussed in the prior section and individual health. Collecting data on discrete exposures can add important detail to understanding how time spent in different contexts affects individual health over time. This will allow epidemiologists to provide more information for public health interventions seeking to improve population health.

Ways forward

Gathering data on the development of social relationships and competing demands on people's time may help identify how to improve social support in populations that have low levels of social resources (low SES, racial/ethnic minority groups). The following section will present eight concepts associated with adding time elements to social epidemiology studies:

Precise data can be collected due to the emergence of digital methods to track respondents. This includes passive location tracking and logging of activities from devices such as smartphones, smartwatches, and fitness trackers.

Ecological Momentary Assessment (EMA) study designs allow for detailed methods and protocols to account for real-time activities.

Daily diaries for public health are well established as discussed above, and can be merged with digital data collection methods to provide more data about decision-making and support examination of intent for time use (e.g. “What would you do more or more often if you could?”).

Combining these methods into longitudinal study designs would allow short-term time-use research across the lifespan to explicate how discrete events lead to larger time trends in people's lives.

Data about time spent on an activity would allow for incorporating time elements into analytic models. For example, incorporating time spent in social situations in health risk assessments may provide additional detail to help understand the social impact on long-term chronic conditions. These analytic models must additionally examine the association of higher-level influences, such as social norms, neighborhood characteristics, and policy environments, and individual health status and public health to provide comprehensive results.

Researchers need to conduct daily time use monitoring and research activities for public benefit. Current comprehensive social and behavioral data collection activities, known more commonly as “surveillance capitalism,” use analytic findings to increase profits and sell goods or services, without informed consent (Zuboff, 2019). Findings should be applied for public benefit. For example, detailed daily time use data may be used to help improve traffic and transportation resources, identify external stressors on mental health, study time spent with adverse environmental exposures, and study how to improve food preparation time.

Researchers need to consider the ethics of collecting highly identifiable information. Based on time use data and other data sources, it may be easy to identify specific research participants. This is especially an issue if research involves sensitive topics, such as substance use, peer relationships, and private time. Researchers must ensure privacy in data collection and reporting.

Potential challenges

Three factors present challenges to implementing recommended research approaches. First, while this commentary defines time in terms of 24-h days there are many ways of experiencing time. For example, social media is a popular activity and is associated with distortions in perceptions of time. People tend to have a distorted sense of time when using social media, both over- and under-reporting their use depending on how much they use (Turel et al., 2018). Additionally, two studies have found that people tend to overestimate their time on social media (Ernala et al., 2020; Verbeij et al., 2021). Riehm et al. (2019) suggested addressing this by assessing ranges of values for time spent on social media (e.g. none, < 30 min, > 30 min, etc.), but this has significant drawbacks for trying to estimate hourly activities throughout the day.

Second, while many technological devices track aspects of time use, they do not provide information about social interactions. For example, wearables such as fitness trackers or smart watches do not provide detailed information on the nature of social relationships, including whether they are positive or negative, length or closeness. To collect all this information, researchers would have to employ multiple data collection methods, such as EMA.

Third, people may not be comfortable providing the extensive data required for the proposals in this commentary. Researchers should work with participants to build trust, and develop robust data collection and reporting procedures that ensure confidentiality.

Conclusion

How people decide to spend time is an important influence on multiple public health issues. While examining disease progression over time has been foundational to epidemiology, social epidemiology could take lessons from prior space-time geography and EMA work, and apply them to social epidemiology and the study of social relations. Specifically, research could focus on how much time people spend in social relationships to develop the protective health benefits of those relationships. Notably, daily time use can provide insights into how exposures are embodied and affect a person's health. Data on decisions that lead to that constellation of time use can provide insights into socially informed decision-making related to health outcomes. Incorporating some time-use data into all epidemiological research has the potential to expand discussions to structural factors affecting all health outcomes.

Footnotes

Acknowledgements

The authors would like to thank the two reviewers for their comments on this manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Craig T Dearfield

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