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. Author manuscript; available in PMC: 2022 Oct 1.
Published in final edited form as: Ment Health Phys Act. 2021 Jun 15;21:100412. doi: 10.1016/j.mhpa.2021.100412

Meaning in Life and Accelerometer-Measured Physical Activity: Association based on 67,038 UK Biobank Participants

Angelina R Sutin 1, Martina Luchetti 1, Yannick Stephan 2, Antonio Terracciano 1
PMCID: PMC8955799  NIHMSID: NIHMS1721425  PMID: 35340340

Abstract

Meaning in life is associated consistently with greater self-reported physical activity. The present research sought to replicate this association with the largest sample to date with objectively measured physical activity. Participants between the ages of 40 and 70 years old from the UK Biobank (N=67,038) wore an accelerometer for up to seven days and reported on their meaning in life. Higher meaning was associated with greater engagement in physical activity, an association robust across age, gender, and education. It remained significant accounting for body mass index, depression, and relative deprivation. Further, for every 1-point increase in meaning in life, there was a 14% increase in likelihood of being in the top quartile of physical activity (OR=1.14, 95% confidence interval=1.11, 1.16, p<.001) and a 10% increase in likelihood of engaging in vigorous activity (OR=1.10, 95% CI=1.06, 1.15, p<.001). Physical activity may be one behavioral mechanism that links meaning in life to better health outcomes.

Keywords: Meaning in life, purpose in life, physical activity, accelerometer

Feeling that one’s life is meaningful has emerged as a consistent predictor of better health outcomes, including greater longevity (Cohen et al., 2016; Czekierda et al., 2017). Physical activity may be one mechanism that contributes to these better outcomes. And, indeed, there is a growing literature that finds that individuals with more meaning also report that they engage in more physical activity (Gomes et al., 2017; Rush et al., 2019). Much of this literature is based on self-reported physical activity. One study has shown that a related construct, purpose in life, is associated with greater physical activity as measured with an accelerometer worn over three days in 104 community volunteers (Hooker & Masters, 2016). This finding suggests a convergence between objective and subjective measures of physical activity. The present research sought to examine whether meaning in life is also associated with accelerometer-measured physical activity. With the largest sample to date (>60,000 participants) with accelerometer-measured physical activity, we further evaluate whether the association differs by age, gender, or education, and the robustness of the association by controlling for potential confounders, including body mass index (BMI), depression, and relative deprivation.

Method

Participants and Procedure

Participants from the UK Biobank (https://www.ukbiobank.ac.uk/) who completed both the accelerometer assessment and the online assessment of meaning in life were included in this study. The UK Biobank is an ongoing cohort study of more than 500,000 individuals. The purpose of the overall study is to improve prevention, diagnosis, and treatment of common diseases. Ethical approval for the UK Biobank was obtained from the North West Multicentre Research Ethics Committee, the National Information Governance Board for Health and Social Care in England and Wales, and the Community Health Index Advisory Group in Scotland. The analysis reported in this paper was based on deidentified data that can be obtained through an application process with the UK Biobank. This research has been conducted using the UK Biobank Resource (Application Reference Number 57672). The baseline assessment for the UK Biobank occurred at 22 assessment centers between 2006 and 2010. A subset of participants aged 40 and older was contacted to wear an accelerometer to measure objective physical activity (age range in the current sample is 40–70). The accelerometer assessment occurred between 2013–2016. Some participants were also asked to complete an online assessment of mental health that included the meaning in life measure. The mental health assessment began in 2016 and is ongoing. A total of 67,038 participants had valid accelerometer and meaning in life data to be included in the present analysis. All participants with valid data on the measures of interest were included in the analytic sample.

Measures

Meaning in life.

Meaning in life was measured with the item, “To what extent do you feel your life to be meaningful?” Participants responded on a 5-point scale from 1 (not at all) to 5 (an extreme amount). Higher ratings thus indicate greater feelings of meaning in life.

Physical activity.

Participants wore a wrist-worn triaxial accelerometer (Axivity AX3, Newcastle upon Tyne, United Kingdom) for up to seven days. The minimum threshold for wear time was 3 days over a 7-day period (the 7-day period was consecutive, but the wear time did not have to be consecutive to be included as valid wear time). About 1.5% of participants wore the accelerometer between 3 and <4 days, 2.5% wore it between 4 and <5 days, 6.1% wore it between 5 and <6 days, 58.5% wore it between 6 and <7 days, and 31.4% wore it for the full 7 days. The vector magnitude of acceleration (milli gravity) was averaged over all five second epochs and was taken as an overall measure of physical activity (higher scores indicate greater physical activity). In addition to this overall measure, the fraction of time spent in moderate and vigorous activity was calculated for each participant and transformed into a score that reflected minutes per day spent in moderate-to-vigorous physical activity (MVPA), defined as percentage of time spent in in 100 mg to 400 mg (moderate) and above 400 mg (vigorous), and a score that contrasted participants who engaged in vigorous activity for at least 1% of the day (14.4 minutes) compared to participants who did not (Ramakrishnan et al., 2021). Detailed information on recruitment, response rate, data collection, and accelerometer data processing in the UK Biobank can be found in Doherty and colleagues (2017).

Covariates.

Covariates were self-reported age at baseline (in years), gender (female=0, male=1), and education (no degree=0, degree=1). BMI was derived as kg/m2 with staff-assessed height and weight measured as part of the physical measure assessment at the UK Biobank Assessment Centre at baseline. Depression concurrent with the meaning in life assessment was measured with the Patient Health Questionnaire (“Over the last 2 weeks, how often have you been bothered by any of the following problems? Feeling down, depressed, or hopeless”) on a scale from 0 (not at all) to 3 (nearly everyday). The items were summed and dichotomized at 10, a recognized threshold for severe depressive symptoms (Arroll et al., 2010). The Townsend deprivation index is an index of several markers that when combined indicate the relative deprivation of an area (Townsend, 1979). In the UK Biobank, the Townsend Deprivation Index was scored for each participant based on their postcode. Self-reported income was the average total household income before tax.

Analytic Strategy

First, we used partial correlation to examine the association between meaning in life and overall physical activity and MVPA, controlling for age, gender, and education. Second, we examined whether these associations varied by age (dichotomized at age 65 to compare middle-aged adults to older adults), gender, and education by testing the difference between two correlations (Preacher, 2002, May) and by testing interaction terms in regression models. Third, we added the additional covariates (BMI, depression, Townsend deprivation index) to evaluate the robustness of the association. Finally, we used logistic regression to examine the association between meaning in life and likelihood of falling within the top quartile of engagement in physical activity and engaging in any vigorous physical activity, controlling for age, gender, and education. SPSS version 26 was used for all analyses.

Results

Descriptive statistics for all study variables are in Table 1. Table 2 shows the association between meaning in life and overall physical activity and MVPA for the sample and by the demographic groups examined. Consistent with the self-report literature, meaning in life was associated with greater physical activity measured objectively with an accelerometer as either overall physical activity or time spent in MVPA. Both associations were significant across age, gender, and education, but it was slightly stronger among women and among participants without a degree. The pattern was the same if moderation was tested in a regression framework for age (i.e., there was no interaction between meaning and age as a continuous variable [physical activity βinteraction=.00, p=.149; MVPA: βinteraction=.00, p=.841]) and education (i.e., there was a significant interaction between meaning and education [physical activity: βinteraction=−.02, p<.001; MVPA: βinteraction=−.02, p<.001]) but not for gender (i.e., the interaction between meaning and gender was not significant [physical activity βinteraction=−.01, p=.173; MVPA: βinteraction=−.01, p=.048]). The overall association was also robust to the inclusion of BMI, depression, and the Townsend deprivation index as additional covariates (n=66,800 due to missing data on some variables; Table 2), and income did not account for the association either (physical activity: rpartial=.070, p<.001, MVPA: rpartial=.059, p<.001; n=60,607 because of missing data on income). Finally, for every one-point increase in meaning in life, there was a 14% increased likelihood that participants would be in the top 25% of the distribution for physical activity (OR=1.14, 95% confidence interval=1.11, 1.16, p<.001), controlling for age, gender, and education and a 10% increased likelihood that participants would engage in vigorous activity (OR=1.10, 95% confidence interval=1.06, 1.15, p<.001).

Table 1.

Descriptive Statistics for All Study Variables

Variable Sample Size Mean (SD) or % (n)
Age (years) 67,038 56.06 (7.71)
Gender (male) 67,038 42.3 (28,332)
Degree (yes) 67,038 45.8 (30,680)
Meaning in life1 67,038 3.70 (.83)
Body mass index (kg/m2) 66,889 26.58 (4.49)
Depression (yes) 67,035 2.3 (1,537)
Townsend Deprivation Index2 66,957 −1.77 (2.78)
Average acceleration3 67,038 28.10 (8.26)
Moderate-vigorous physical activity (minutes/day) 67,038 109.97 (46.77)
Vigorous activity (≥1%) 67,038 6.4 (4,277)
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Note.

1

Rated on a scale from 1 (not at all) to 5 (an extreme amount).

2

Higher scores indicate more deprivation.

3

Vector magnitude of acceleration averaged over seven days.

Table 2.

Association Between Meaning in Life and Physical Activity

Physical Activity Moderate-Vigorous Physical Activity
Meaning in life .072**1 .060**2 .061**1 .050**2
 By age <65 years old ≥65 years old <65 years old ≥65 years old
.072**1 .072**1 .060**1 .061**1
 By gender Female Male Female Male
.079**3 .065**3 .066**3 .053**3
 By education No degree Degree No degree Degree
.086**4 .056**4 .072**4 .045**4
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Note. N=67,038. All values are partial correlations.

1

Partial correlation controlling for age (continuous), gender, and education.

2

Partial correlation controlling for body mass index, depression, the Townsend Deprivation Index and age, gender, and education (n=66,800 due to missing data on some variables).

3

Partial correlation controlling for age (continuous) and education.

4

Partial correlation controlling for age (continuous) and gender.

Discussion

The present study reports the largest sample to date with meaning in life and physical activity measured by accelerometer. Meaning in life was associated with greater physical activity, an association apparent across demographic groups, although slightly stronger among individuals without a degree. The association was also robust to common confounders.

Meaning in life is the broad sense that one’s life is coherent, purposeful, and significant and is a core component of eudaimonic well-being (Martela & Steger, 2016). It is conceptually similar to purpose in life, which is generally considered a subcomponent of meaning (George & Park, 2013). Although theoretically distinct, both purpose and meaning have been empirically associated with better physical health, including objective as well as subjective markers of health, with similar effect sizes (Czekierda et al., 2017; Sutin et al., 2021). As such, in relation to health behaviors and outcomes, meaning and purpose share similar protective effects.

There are likely to be multiple pathways through which meaning leads to better health outcomes. Behavioral mechanisms, such as physical activity, are considered one prominent pathway (Steptoe, 2019). And, indeed, across diverse populations, higher meaning in life has emerged as a predictor of greater self-reported physical activity (Gomes et al., 2017; Rush et al., 2019). The related literature on purpose in life has found similar positive associations (Kim et al., 2020) and has been further associated with greater physical activity as measured by accelerometer (Hooker & Masters, 2016). The present research supports this association with the largest sample to date with meaning in life. This research also found demographic differences to be one of degree rather than of kind (e.g., the association was stronger among individuals without a degree, but the association among individuals with a degree was still apparent). This pattern suggests that meaning is associated widely with greater engagement in physical activity.

The association between meaning and physical activity was robust. Body weight and depression have been implicated in the related construct of purpose in life (Kim et al., 2020; Laird et al., 2019) and in physical activity (Schuch et al., 2017; Tudor-Locke et al., 2010). These factors, however, had only a modest effect on the association between meaning and physical activity and did not account for all of it. Socioeconomic factors (both environmental and personal) likewise did not account for this relation. There may thus be other mechanisms that contribute to this association. Individuals higher in the related construct of purpose, for example, feel more intrinsically motivated to engage in physical activity and value it more than individuals lower in purpose (Sutin et al., 2021). In addition, higher meaning in life has been associated with greater belief in one’s ability to be physically active (i.e., self-efficacy), which has been found to be one mechanism that accounts for the relation between meaning and physical activity (Rush et al., 2019). Motivational pathways may thus better explain the relation between meaning and being more physically active than through more clinical pathways.

Meaning in life is associated with better health outcomes in older adulthood, including lower risk of cognitive impairment (Sutin et al., 2020) and lower risk of premature mortality (Cohen et al., 2016). The robust association with physical activity may be one mechanism that links meaning to better outcomes. Physical activity, for example, is one modifiable factor that protects against dementia (Norton et al., 2014) and is associated with greater longevity (Ekelund et al., 2019). Given that meaning is also modifiable (Park et al., 2019), it may be a useful target of intervention. That is, interventions to increase meaning may also be effective to increase time spent engaging in physical activity, ultimately leading to better health outcomes.

There is evidence for bidirectional associations between the related construct of purpose and physical activity (Yemiscigil & Vlaev, 2021): Individuals who feel more purposeful increase in physical activity over time and individuals who engage in more physical activity increase in feelings of sense of purpose over time. The same pattern is likely true for meaning in life. Individuals who feel more meaning may have more motivation and commitment to being physically fit that may help sustain physical activity over time. There is also evidence from an intervention study to increase physical activity that engaging in more physical activity increases the related construct of purpose (Delextrat et al., 2016). It is likely that there is a feedback loop that strengthens over time: Feeling that one’s life is meaningful may lead to more engagement and activity, and this activity may feed back into feeling that one’s life is more meaningful.

The present study had several strengths, including the large sample size and the objective measurement of physical activity with an accelerometer. Limitations include the single-item measure of meaning, the measurement of physical activity prior to the measurement of meaning, and that both variables were measured only once. As such, it was not possible to test the potential bi-directional associations. Future research would benefit from including longer measures of both meaning and purpose and longitudinal assessments of meaning/purpose and physical activity. In addition, although the UK Biobank sample is large, it is not representative and thus the results may not generalize to other populations. The association, however, is similar to what has been found previously with purpose and self-reported physical activity in samples that had more diversity and were from a different country (Sutin et al., 2021; Yemiscigil & Vlaev, 2021). Despite these limitations, the present research indicates that meaning in life is associated with objectively measured physical activity in the largest sample to date and that this association generalizes across sociodemographic populations.

Highlights.

  • A feeling of purpose and meaning is associated with self-reported physical activity

  • Initial work suggests it is also related to accelerometer-measured physical activity

  • We examine this association in the large UK Biobank sample (N=67,038)

  • Meaning in life was associated with greater accelerometer-measured physical activity

  • This association was apparent across demographic groups and robust to confounders

Acknowledgments

Funding: Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG053297. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Availability of data and material: Data can be obtained from the UK Biobank (https://www.ukbiobank.ac.uk/). The UK Biobank does not allow distribution of its data. Authors’ contributions: ARS conceptualized the study, analyzed the data, and wrote the manuscript. ML, YS, AT provided critical feedback and helped draft the manuscript

Conflicts of interest/Competing interests: None

Conflict of Interest

The authors have no conflicts of interest to report.

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