Abstract
Objective:
To determine the association between meaning in life and all-cause and cause-specific mortality, and whether associations vary by depression or sociodemographic factors.
Methods:
Participants were UK Biobank cohort members who reported on their meaning in life in the mental health assessment from October 2016 to July 2017 (N=153,505). All-cause mortality and cause-specific mortality were identified from ICD-10 codes from national death registries through December 2022.
Results:
Over the up to six-year follow-up, every standard deviation higher in meaning in life was associated with a 15% decreased risk of death from any cause (HR=.87, 95% CI=.85-.90, p<.001). The association was attenuated but remained significant accounting for socioeconomic, clinical, and behavioral risk factors (HR=.91, 95% CI=.88-.94, p<.001). Meaning in life was associated with reduced risk of death from 7 of the 8 cause-specific deaths examined: external cause (47%), respiratory (41%), nervous (32%), digestive (25%), or circulatory (15%) systems, COVID-19 (28%), and cancer (8%). Depression concurrent with the meaning assessment did not explain or moderate these associations, which indicated that meaning was similarly protective when concurrently experiencing psychological distress. The association between meaning and all-cause mortality was similar across age, ethnicity, and socioeconomic status but slightly stronger among female than male participants.
Conclusion:
Feeling that one’s life has meaning is associated with lower risk of mortality, particularly causes of death due to the respiratory system, nervous system, or COVID-19. Given that meaning in life can be modified through intervention, future research could address whether it could be a useful target of intervention.
Keywords: Meaning in life, Purpose in life, Premature mortality, Longevity, Cause-specific death
Introduction
Feelings of meaning and purpose are one critical component of eudaimonic well-being.1 Such feelings contribute to better mental health2 and are part of the definition of human flourishing.3 There is also consistent evidence that greater feelings of meaning and purpose in life are associated with better physical health outcomes, including longevity: Across countries, measures, and timeframes, a more meaningful life is a longer one.4–6 This association may be due, in part, to healthier lifestyles associated with meaning and purpose, including greater engagement in physical activity7 and less use of substances,8 as well as healthier clinical profiles, including fewer diseases9 and better regulation of blood sugar10 and blood pressure.11
In addition to all-cause mortality, emerging work suggests that these feelings may also be associated with specific causes of death. There is most evidence that meaning is associated with lower risk of death due to cardiovascular factors12–14 and preliminary evidence for an association with lower risk of death from digestive causes but not death due to cancer or respiratory causes.14 Meaning and purpose may thus not be protective for all types of deaths. Indeed, all deaths are not the same, and identifying risk factors for specific causes of death will help develop more targeted interventions to reduce risk of premature mortality.15
The present study examines the association between meaning in life and common causes of death, in addition to all-cause mortality, in the UK Biobank, a large, prospective, population-based cohort. Of particular note, with meaning in life measured before the pandemic and cause of death available up to December 2022, we include COVID-19 as a specific cause of death, in addition to other prevalent causes of death that range from cancer to external causes. In addition to COVID-19, the present research extends previous research on meaning in life and mortality because it considers a broader range of causes of death, uses a larger sample size, systematically addresses the role of socioeconomic, clinical, and behavioral risk factors in this association, and evaluates depression as a covariate and moderator of the association. We test for moderation by age, sex, ethnicity, and education to evaluate whether the associations were similar or varied across these sociodemographic groups. We further test for moderation by depression to determine whether feelings of distress erode the protective association of meaning or whether meaning may be a resource for longevity despite significant psychological distress.
Method
Participants and Procedure
This study used data from the UK Biobank study of the prevention, diagnosis, and treatment of common diseases (http://www.ukbiobank.ac.uk). At the 2006-2010 baseline assessment, more than 500,000 individuals registered with the UK National Health Service (NHS) were recruited and tested at 22 assessment centers across the UK. In 2016, active participants with a valid email address were invited to complete an online mental health assessment that included the measure of meaning in life.16 Participants provided written informed consent before completing the questionnaire. The present analysis was based on up to 153,505 UK Biobank participants who completed this measure. Ethical approval for the UK Biobank was obtained from the North West Multicenter Research Ethics Committee. All participants gave informed consent. This research was conducted using the UK Biobank Resource (Application Reference Number 57672). Data are available through an application to the UK Biobank; analytic scripts for the analysis are in supplemental material.
Measures
Meaning in life.
Meaning in life was measured with the item, “To what extent do you feel your life to be meaningful?” on a 5-point scale with the response options 1 (not at all), 2 (a little), 3 (a moderate amount), 4 (very much), and 5 (an extreme amount). Higher ratings indicated greater feelings of meaning. The rating was standardized to facilitate interpretation such that the coefficient reflects a one-SD difference in meaning. This item has been used successfully in previous research17 and has been shown to have statistically similar associations with longer measures.18
Mortality.
The UK Biobank obtained date and cause of death from two national death registries: the NHS for participants in England and Wales and the NHS Central Register of the National Records of Scotland for participants in Scotland. Death data from these sources were reported with ICD-10 coded cause of death. All-cause mortality was considered as death from any cause. Cause-specific deaths were classified as cancer (C00-C97), diseases of the circulatory system (I01-I89), nervous system (F00-F89, G00-G99), respiratory system (J00-J99), digestive system (K00-K93), COVID-19 (U07.1-U07.2), infectious disease other than COVID-19 (A00-B99), and external causes of death (V01-Y89). In supplemental analyses, self-harm (codes X60-X84) was also considered as an outcome.
Covariates.
Demographic covariates were age in years (standardized), sex (0=male, 1=female), and ethnicity (0=white, 1=person of color). Socioeconomic covariates were university degree or equivalent (0=no, 1=yes) and the Townsend deprivation index, a neighborhood measure of socioeconomic status based on participant postcodes (standardized). Clinical risk factors were obesity (body mass index ≥30 kg/m2 based on staff-assessed weight and height, 0=no, 1=yes) and reported diagnosis of diabetes (0=no, 1=yes) and hypertension (0=no, 1=yes). Behavioral risk factors were smoking status (two dummy coded variables that compared former=1 and current=1 to never=0), alcohol consumption (two dummy coded variables that compared former=1 and current=1 to never=0), and physical activity (0=did not meet the recommendation for moderate/vigorous activity, 1=did meet recommendation for moderate/vigorous activity). Depression was measured with the Patient Health Questionnaire-9 and categorized into no probable depression (=0) and passed the threshold for probable depression (=1) based on a standard threshold (PHQ≥10).19 Note that this threshold has been validated to identify depression,19 but it is not a clinician diagnosis of depression.
Analytic Approach
Cox regression was used to test the association between meaning in life and risk of all-cause and cause-specific mortality. Time to death was calculated from the date of the assessment of meaning in life to date of death. Time was censored at the date of the last death reported (December 20, 2022) for all participants who were still alive. The interaction term between log(time) and meaning was not significant (p=.868), which indicated that the proportional hazard assumption was not violated. Model 1 tested the association between meaning and risk of mortality controlling for age, sex, and ethnicity. Since a one standard-deviation difference in meaning corresponds to less than a unit difference in the response scale, we also report Model 1 using the raw metric of meaning in life so that the HR can be interpreted as a one-unit difference in the response scale of the measure. In addition, in a supplemental analysis, we entered meaning in life as a categorical variable, with the first response option (not at all) as the reference group to examine the association for each response option of the predictor. Model 1.1 was a sensitivity analysis that excluded participants who died within one year of their meaning assessment. Model 2 was Model 1 with the addition of socioeconomic factors (education, deprivation). Model 3 was Model 2 with the addition of clinical risk factors (obesity, diabetes, hypertension). Model 4 was Model 3 with the addition of behavioral risk factors (smoking, alcohol). Model 4.1 was Model 4 with the addition of physical activity; physical activity was added in a separate model because of the amount of missing data for this variable. These models were repeated for cause-specific mortality with an additional sensitivity analysis that tested competing risk to evaluate robustness of cause-specific mortality associations (Model 1.2). All cases with relevant data were included in each set of analyses. We next tested whether the association between meaning in life and mortality was independent of depression concurrent with the measurement of meaning and whether the association was moderated by depression. Depression was added as a covariate to Model 1, and an interaction term between meaning and depression was added in a second step to evaluate whether the association between meaning and both all-cause and cause-specific mortality was similar or different depending on concurrent depression status. We likewise tested whether the sociodemographic factors moderated the association between meaning and all-cause mortality. Finally, in a supplemental analysis, we reran all models with self-harm as the specific cause of death.
Results
Descriptive statistics are in Table 1. The follow-up period ranged from .01 to 6.44 years (943,684 person-years). A total of 5,240 participants died during this period. The average time to death for these participants was 3.61 years (range .01-6.33 years), and the average age of death was 69.11 (range=47.13-79.69). These deaths occurred before the UK life expectancy (approximately 80 years old),20 which suggested that most deaths were premature.
Table 1.
Descriptive Statistics for the Total Sample and by Mortality Status
| Variable | Total Sample | Mortality Status |
|
|---|---|---|---|
| Alive | Dead | ||
| Age | 64.02 (7.72) | 63.84 (7.71) | 69.11 (6.30) |
| Age range | 46.46-80.71 | 46.46-80.71 | 47.13-79.69 |
| Sex (female) | 56.8% (87,240) | 57.4% (85,030) | 42.2% (3030) |
| Ethnicity (person of color) | 3.2% (4,918) | 3.2% (4790) | 2.4% (128) |
| Education (degree) | 45.3% (69,476) | 45.5% (67394) | 39.7% (2082) |
| Deprivation (n=153,309) | −1.71 (2.83) | −1.72 (2.82) | −1.56 (2.97) |
| Meaning in life | 3.69 (.83) | 3.70 (.83) | 3.61 (.85) |
| Not at all | 1.7% (2605) | 1.7% (2496) | 2.1% (109) |
| A little | 5.9% (9099) | 5.9% (8723) | 7.2% (376) |
| A moderate amount | 26.6% (40873) | 26.5% (39362) | 28.8% (1511) |
| Very much | 52.8% (81019) | 52.8% (78344) | 51.0% (2675) |
| An extreme amount | 13.0% (19909) | 13.0% (19340) | 10.9% (569) |
| Obesity (yes) (n=153130) | 19.8% (30,341) | 19.5% (28865) | 28.2% (1476) |
| Diabetes (yes) (n=153,233) | 3.3% (5070) | 3.1% (4620) | 8.6% (450) |
| Hypertension (yes) (n=153,431) | 21.8% (33,502) | 21.3% (31643) | 35.5% (1859) |
| Smoking status | |||
| Former (yes) | 35.1% (53,841) | 34.8% (51570) | 43.3% (2271) |
| Current (yes) | 7.2% (11,036) | 7.0% (10433) | 11.5% (603) |
| Alcohol status (n=153,366) | |||
| Former | 2.7% (4,173) | 2.7% (3948) | 4.3% (225) |
| Current | 94.3% (144,826) | 94.4% (139995) | 92.2% (4831) |
| Physical activity (yes) (n=127,838) | 44.8% (68,732) | 44.9% (66552) | 51.1% (2180) |
| Depression (yes) (n=150,796) | 5.6% (8621) | 5.5% (8170) | 8.6% (451) |
| All-cause mortality | 3.4% (5,240) | -- | 11% (5240) |
| Time | 6.15 (.59) | 6.24 (.15) | 3.61 (1.69) |
| Time range | .01-6.44 | 5.40-6.44 | .01-6.33 |
| Cause-specific death | |||
| Cancer | 1.9% (2878) | -- | -- |
| Circulatory system | .7% (1017) | -- | -- |
| Nervous system | .20% (308) | -- | -- |
| Respiratory system | .20% (315) | -- | -- |
| Digestive system | .10% (142) | -- | -- |
| COVID-19 | .10% (205) | -- | -- |
| Infectious diseases | .03% (41) | -- | -- |
| External causes | .10% (79) | -- | -- |
Note. N=153,505, unless otherwise noted.
The association between meaning in life and risk of all-cause and cause-specific mortality is in Table 2. Every standard deviation higher in meaning in life was associated with an approximately 15% reduced risk of premature mortality (18% when the HR corresponded to a one-point difference in meaning using the raw response scale). The supplemental analysis indicated that compared to the reference group (response option, “not at all”), participants who reported a moderate amount, very much, and an extreme amount of meaning in life had lower risk of mortality (Supplemental Table S1). The association was similar when deaths that occurred within one year of the assessment of meaning were excluded from the analysis. This association was attenuated but remained significant in models that progressively controlled for SES (the results were identical when education was entered as a continuous rather than dichotomous variable; Supplemental Table S2) and clinical and behavioral risk factors. Collectively, the SES, clinical, and behavioral factors attenuated the association by about 33% ((HRmodel1 − HRmodel4.1)/(HRmodel1 − 1)) x 100).
Table 2.
The association between meaning in life and risk of all-cause and cause-specific mortality
| Model | All-cause | Cancer | Circulatory system | Nervous system | Respiratory system |
|---|---|---|---|---|---|
| Model 1, # cases | 5240/148265 | 2878/150626 | 1017/152484 | 308/153117 | 315/153190 |
| Model 1, HR (95% CI) | .87 (.85-.90) | .93 (.90-.96) | .87 (.82-.93) | .76 (.68-.85) | .71 (.64-.79) |
| Model 1, HR (95% CI)a | .85 (.82-.88) | .92 (.88-.96) | .85 (.79-.91) | .72 (.63-.82) | .66 (.59-.75) |
| Sensitivity | |||||
| Model 1.1, # cases | 4782/148265 | 2609/150438 | 919/152124 | 293/152746 | 288/152673 |
| Model 1.1, HR (95% CI) | .88 (.85-.90) | .93 (.89-.96) | .88 (.83-.94) | .78 (.69-.87) | .72 (.65-.80) |
| Model 1.2, # cases | -- | 2878/150626 | 1017/152484 | 308/153117 | 315/153190 |
| Model 1.2, HR (95% CI) | -- | .92 (.88-.96) | .85 (.79-.91) | .72 (.64-.82) | .67 (.59-.75) |
| Socioeconomic status | |||||
| Model 2, # cases | 5236/148073 | 2875/150433 | 1017/152288 | 307/152922 | 315/152994 |
| Model 2, HR (95% CI) | .88 (.86-.91) | .93 (.90-.97) | .88 (.83-.94) | .76 (.68-.84) | .74 (.66-.81) |
| Clinical factors | |||||
| Model 3, # cases | 5198/147488 | 2862/149823 | 1004/151678 | 304/152303 | 312/152374 |
| Model 3, HR (95% CI) | .89 (.87-.92) | .94 (.90-.98) | .91 (.86-.97) | .76 (.68-.84) | .75 (.68-.83) |
| Behavioral factor | |||||
| Model 4.1, # cases | 5196/147426 | 2861/149760 | 1004/151614 | 304/152239 | 311/152311 |
| Model 4.1, HR (95% CI) | .90 (.88-.93) | .95 (.92-.99) | .92 (.86-.98) | .76 (.68-.84) | .77 (.70-.86) |
| Model 4.2, # cases | 4238/122973 | 2351/124859 | 826/126381 | 244/126905 | 246/126965 |
| Model 4.2, HR (95% CI) | .91 (.88-.94) | .95 (.92-.99) | .92 (.86-.99) | .76 (.67-.86) | .82 (.73-.92) |
| Model | Digestive system | COVID-19 | Infectious diseases | External causes |
|---|---|---|---|---|
| Model1, # cases | 142/153324 | 205/151407 | 41/153334 | 79/153424 |
| Model 1, HR (95% CI) | .80 (.69-.94) | .78 (.68-.89) | .89 (.65-1.24) | .68 (.56-.83) |
| Model 1, HR (95% CI)a | .77 (.64-.93) | .74 (.63-.87) | .87 (.60-1.26) | .63 (.50-.80) |
| Sensitivity analyses | ||||
| Model 1.1, # cases | 131/152876 | 205/151407 | 37/152993 | 62/152985 |
| Model 1.1, HR (95% CI) | .82 (.69-.97) | .78 (.68-.89) | .88 (.64-1.21) | .72 (.57-.91) |
| Model 1.2, # cases | 131/152876 | 205/151407 | 37/152993 | 62/152985 |
| Model 1.2, HR (95% CI) | .77 (.64-.93) | .74 (.64-.87) | .87 (.60-1.26) | .63 (.50-.80) |
| Socioeconomic status | ||||
| Model 2, # cases | 142/153128 | 205/151211 | 41/153138 | 79/153228 |
| Model 2, HR (95% CI) | .83 (.71-.97) | .80 (.70-.91) | .91 (67-1.24) | .68 (.56-.83) |
| Clinical risk factors | ||||
| Model 3, # cases | 142/152506 | 204/150599 | 41/152516 | 78/152606 |
| Model 3, HR (95% CI) | .85 (.72-.99) | .81 (.72-.93) | .92 (.68-1.25) | .68 (.56-.83) |
| Behavioral risk factors | ||||
| Model 4, # cases | 142/152442 | 204/150536 | 41/152452 | 78/152542 |
| Model 4, HR (95% CI) | .87 (.74-1.02) | .82 (.72-.94) | .94 (.69-1.27) | .70 (.57-.85) |
| Model 4.1, # cases | 116/127024 | 160/125513 | 30/127081 | 68/127141 |
| Model 4.1, HR (95% CI) | .81 (.68-.96) | .82 (.71-.96) | .90 (.63-1.30) | .67 (.55-.83) |
Note. Coefficients are hazard ratios and 95% confidence intervals. Model 1 controls for age, sex, and ethnicity. Model 1.1 excluded participants who died within one year of their meaning assessment. Model 1.2 was the competing risk model for cause-specific mortality. Model 2 was Model 1 with education and deprivation. Model 3 was Model 2 with obesity, diabetes, and hypertension. Model 4 was Model 3 with smoking and alcohol. Model 4.1 was Model 4 with physical activity.
The same analysis as Model 1 but with the response scale for meaning in life such that the HR corresponds to a one-unit difference in the raw response scale instead of a one standard deviation difference in meaning.
Table 2 also shows the association between meaning in life and cause-specific mortality. Meaning was associated with 7 of 8 causes of death. Specifically, every SD in meaning was associated with an 8% to 47% lower risk of death from cancer, circulatory system, nervous system, respiratory system, digestive system, COVID, or an external cause of death. Meaning was unrelated to mortality due to an infectious disease other than COVID. Similar to all-cause mortality, the association between meaning and cause-specific mortality remained significant excluding participant deaths within one year of the meaning assessment. The association also remained significant for all cause-specific deaths in the competing risk model. The associations were progressively attenuated with the inclusion of the SES, clinical, and behavioral factors. The only association that was reduced to non-significance when the behavioral covariates were included in the model was death due diseases of the digestive system. As with Model 1, meaning was unrelated to mortality due to infectious disease other than COVID in the supplemental and progressively controlled models.
Depression generally did not account for the association between meaning and mortality: All-cause and most cause-specific associations remained significant with the inclusion of depression as a covariate (Table 3). Death due to the digestive system was reduced to non-significance; deaths due to infectious diseases other than COVID remained non-significant. The association between meaning and all-cause mortality and the six other cause-specific deaths remained significant. None of the interactions between meaning and depression on risk of death was significant. None of the interactions between meaning and the sociodemographic factors on all-cause mortality was significant, except for sex (Supplemental Table S3): The association was apparent for both males and females but was slightly stronger among females (HRfemales=.84, 95% CI=.81-.88, p<.001; HRmales=.90, 95% CI=.87-.93, p<.001).
Table 3.
Meaning in life and Mortality controlling for Depression and Interaction with Depression
| Cause of death | Sample size | Controlling for depression | Interaction with depression |
|---|---|---|---|
| All-cause | 5103/145693 | .92 (.90, .95) | 1.08 (.99-1.18) |
| Cancer | 2828/147967 | .95 (.92, .99) | 1.11 (.98-1.26) |
| Circulatory system | 996/149796 | .92 (.86-.98) | 1.12 (.92-1.36) |
| Nervous system | 283/150436 | .87 (.77-.98) | 1.23 (.92-1.66) |
| Respiratory system | 298/150498 | .80 (.72-.90) | 1.08 (.81-1.45) |
| Digestive system | 139/150619 | .93 (.78-1.11) | 1.08 (.71-1.62) |
| COVID-19 | 196/148756 | .82 (.72-.96) | .94 (.61-1.47) |
| Infectious diseases | 40/150632 | 1.00 (.72-1.39) | 1.26 (.55-2.91) |
| External causes | 78/150716 | .80 (.64-.99) | .86 (.51-1.44) |
Note. Coefficients are hazard ratios and 95% confidence intervals. Analysis controlled for age, sex, and ethnicity.
Finally, the sample size for self-harm was small (n=26). Still, the association between meaning and death by self-harm was as expected: Every SD higher in meaning was associated with 82% lower risk of death by self-harm (HR=.55, 95% CI=.41-.76), an association that persisted controlling for SES (HR=.57, 95% CI=.42-.78), clinical risk factors (HR=.57, 95% CI=.42-.78), and behavioral risk factors (HR=.60, 95% CI=.43-.82), including physical activity (HR=.58, 95% CI=.42-.81). It was also independent of concurrent depression (HR=.70, 95% CI=.49-.99) and not moderated by depression (HRinteraction=1.07, 95% CI=.52-2.18). It was, however, reduced to non-significance when deaths within one year of the meaning assessment were excluded (HR=.71, 95% CI=.45-1.10, p=.12), although the sample size for this analysis was particularly small (n=15 deaths).
Discussion
This research provides the first comprehensive test of the association between meaning in life and all-cause and cause-specific risk of death. In addition to all-cause mortality, participants with higher meaning in life had lower risk of death from nearly every specific cause tested: Cancer, the circulatory, nervous, respiratory, or digestive systems, COVID-19, and an external cause. These associations were slightly attenuated compared to the competing risks model. The association remained significant controlling for socioeconomic, clinical, and behavioral factors for all causes of death, except the digestive system. Notably, higher meaning was associated with lower risk of death from COVID-19 and self-harm.
A sense that one’s life has meaning and purpose is one critical component of eudaimonic well-being that is distinct from feelings of happiness or sadness.21 Meaning and purpose may help to select and structure goals in one’s life and the striving to achieve those goals,22 which may have an advantage for health.23 This process may lead to several pathways to greater longevity. First, there is a robust association between meaning and health-promoting behaviors that suggests a behavioral pathway. Meaning in life, for example, is associated consistently with greater engagement in physical activity, whether measured with self-report24 or accelerometer7 and less use of substances, such as nicotine.25 Another potential pathway is through healthier clinical factors. Individuals with more meaning and purpose, for example, have less disease burden,9 healthier inflammatory profiles,26 and better glucose regulation.10 Accounting for behavioral and clinical factors attenuated the association between meaning and premature mortality but did not account completely for it. This pattern suggests that there are likely to be other pathways. Meaning in life, for example, is associated with better regulation of stressors27 and lower perceived stress28 that may help support greater longevity.29 When facing setbacks, people with a stronger sense of meaning are more likely to perceive everyday stressors as more manageable and engage in more adaptive coping strategies.30 Greater meaning in life may also be a motivational force that serves greater longevity by virtue of the long-term goal pursuit associated with it. That is, striving to attain long-term goals may become something akin to a self-fulfilling prophecy where more life is needed to accomplish personally meaningful goals. These pathways are likely to be common and relevant across most causes of death, which is supported by the analysis of cause-specific death that largely pointed to the broad protective association for meaning on reduced risk of premature mortality, regardless of cause.
Previous work on meaning and purpose in life and cause-specific mortality has focused primarily on death due to cardiovascular causes.6 A previous meta-analysis of five samples, for example, found meaning and purpose to be associated with lower risk of cardiovascular death.4 This protective association is not surprising since meaning and purpose have long been associated with cardiovascular health, including fewer vascular risk factors,31 cardiovascular events,4 and better regulation of blood pressure.11 Notably, the association between meaning and lower risk of premature mortality was independent of common clinical and behavioral risk factors for cardiovascular death, which indicates that this association is not due entirely to shared risk factors.
Meaning in life was also associated with lower risk of death due to cancer, which is inconsistent with a previous study in the HRS that did not find this association.14 The deaths due to cancer in the present study were over 10-fold higher (n=2878 vs n=208) than in the previous published study, and thus the UK Biobank may have been better powered to detect an association. Much research has focused on meaning making among individuals with cancer.32 Many interventions, for example, help patients find meaning in their diagnosis and treatment.33 Such interventions may help to prolong life in addition to coping with diagnosis and treatment. Feelings of meaning and purpose are also associated with greater use of cancer screenings34 that may help to detect cancer early and thus contribute to greater longevity.
There is a robust literature on meaning in life and lower risk of neurodegenerative diseases, such as dementia18 and Parkinson’s disease.35 Consistent with this literature, meaning was associated with lower risk of death from nervous system diseases. Meaning and purpose support cognitive, behavioral, and social processes that help keep the brain healthy.36 In particular, in addition to the clinical and behavioral pathways that are likely to support greater longevity across causes, the social and cognitive activity associated with meaning37 may be particularly important to prevent or delay diseases of the nervous system, especially neurodegenerative diseases.38 The present findings indicate that this protective association against incident neurodegenerative diseases persists through death from neurological causes.
The present study is the first to test an association between meaning in life and premature mortality due to COVID-19. The assessment of meaning took place well before the onset of the pandemic. As such, there is no possibility of reverse causality because participants reported their meaning before SARS-CoV-2 existed. The finding that participants who felt their life meaningful were 28% less likely to die from COVID-19 complements the literature on preventative behavior during the pandemic. Feelings of meaning and purpose, for example, were associated with preventative behavior, such as hand-washing and mask wearing39 and more intention to get the COVID-19 vaccine.40 As with other causes of death, the clinical and behavioral profiles of individuals with more meaning may have helped protect them during the pandemic. Notably, however, the association persisted after accounting for shared risk factors for COVID-19 deaths (e.g., obesity, diabetes).
Meaning in life was associated with lower risk of death from external causes. As with COVID-19, the preventative mindset of individuals with more meaning may help reduce the likelihood of precarious situations. Although the sample size was very small and thus the association should be interpreted with caution, meaning was associated with a lower risk of death from self-harm. Feelings of meaning, even during periods of suicidal ideation, are protective against increases in ideation and suicide attempts,41 which may be one mechanism through which meaning is associated with lower risk of death through self-harm and helps reduce suicidality among individuals experiencing distress.42 The sensitivity analysis that excluded deaths within one year of the meaning assessment suggests that loss of meaning may be one process of suicidal ideation that culminates in suicide.
Although meaning and purpose are often equated with mental health or a lack of depression, meaning is more than simply feelings of happiness or lack of sadness.21 There is, however, an association between meaning and depression,43 and individuals experiencing depression tend to feel that their life is less meaningful than individuals without depression.44 Even when distressed, however, a greater sense of meaning is associated with better longitudinal outcomes.45 In the present analysis, the inclusion of depression attenuated the association between meaning and mortality, but in most cases, the association remained significant. Most notably, the association was not moderated by depression, which indicated that meaning was associated with lower risk of death even for people experiencing psychological distress. The only evidence of moderation that we found was for sex, which indicated that the protective association between meaning and all cause-mortality was slightly stronger among females. Interestingly, this moderation replicates a previous, similarly small, sex difference reported in the literature.46
The present research had several strengths, including the large sample, the prospective follow-up, and the ability to test the association with many specific causes of death. There are also limitations. First, the length of follow-up was relatively short. Although consistent with previous research on meaning and mortality,4 a longer follow-up is needed to reduce the possibility of reverse causation and for more deaths to occur. Second, the analysis for some specific causes of death was underpowered because the number of deaths was small. Third the UK Biobank sample is from one high-income country and is not representative of the UK. This research needs to be extended to other populations, particularly from lower- and middle-income countries and more representative samples. Despite these limitations, the present research demonstrates that greater feelings of meaning in life are associated with greater longevity across a range of causes of death.
Supplementary Material
Funding:
Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG074573. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Credit Statement
Sutin: Conceptualization, Data curation, Formal analysis, Funding acquisition, Writing - original draft
Luchetti: Conceptualization, Writing - review & editing
Karakose: Conceptualization, Writing - review & editing
Stephan: Conceptualization, Writing - review & editing
Terracciano: Conceptualization, Data curation, Formal analysis, Writing - review & editing
Conflicts of interest/Competing interests: The authors have no competing interests to report.
This research was conducted using the UK Biobank Resource (Application Reference Number 57672). Data can be obtained from the UK Biobank (https://www.ukbiobank.ac.uk/). The UK Biobank does not allow distribution of its data.
References
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