Case Study | The Impact of Loneliness on Health
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Case Studies
Unpacking the lived experience: How loneliness can affect our health
The problem
The U.S. Surgeon General recently labeled loneliness and social isolation an epidemic and a public health crisis, highlighting the detrimental role of loneliness in health and well-being.1 As an important social determinant of health (SDOH), loneliness has been linked with a risk for Parkinson’s disease2; worsening chronic pain3; all-cause, cancer-specific, and cardiac-related mortality;4 and more.
However, we do not completely understand the inter-relationships between loneliness and disease risk, partially due to the lack of a standardized definition, inconsistent monitoring, and an insufficient evidence base. Calls to address these limitations aim to support decision-making for interventions that could alleviate the public health burden of loneliness and social isolation.5
Loneliness is a complex construct, and its measurement and solutions should reflect the diverse lived experiences of individuals experiencing loneliness. A combination of self-reported and wearable data could more accurately highlight novel trends and associations between loneliness and overall health.
The survey and wearable data
A survey initially rolled out in July 2023 on the Evidation direct-to-participant platform gathered information about well-being, and we analyzed data from the first 95,000 respondents. The survey included a question about loneliness: “How often during the past two weeks have you felt lonely?” Response options were “None or almost none of the time,” “Some of the time,” “Most of the time,” “All or almost all of the time,” and “I don’t know.”
We then explored the lived experience with loneliness using the response to that question for the 68,000 people who also had at least 30 days of step and heart rate data connected with the Evidation platform during July and August.
Findings
Over one-half (52%) of respondents reported feeling lonely at least some of the time, with trends in the frequency of loneliness evident across multiple dimensions.
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
- 67% of young adults (18-25 years) reported feeling lonely at least some of the time.
- 31% of older adults (60+ years) reported feeling lonely at least some of the time.
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
- 71% of individuals who identify as non-binary reported feeling lonely at least some of the time.
- 52% and 47% of women and men, respectively, reported feeling lonely at least some of the time.
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
- 42% of those who reported being lonely “All or almost all of the time” reported not receiving support from someone close, compared with 12% among those who were lonely “None or almost none of the time.”
Depressive and anxiety symptoms
A trend between loneliness and more severe depressive and anxiety symptoms was also observed using responses to the Patient Health Questionnaire-8 (PHQ-8) and Generalized Anxiety Disorder-7 (GAD-7). For both measures, higher scores indicate greater symptom severity.
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Individuals who reported a greater frequency of loneliness also self-reported more sleep conditions such as insomnia and had shorter wearable-collected sleep durations, a trend which was more pronounced with age:
- Self-reported sleep conditions were twice as prevalent among those who were more often lonely (“All or almost all of the time”: 21% vs. “None or almost none of the time: 11%)
- Older adults (60+ years) experienced a 36-minute difference in average sleep duration between those who were lonely “None or almost none of the time” and those who were lonely “All or almost all of the time”, after excluding people with diagnosed sleep conditions.
Activity levels
A higher frequency of loneliness was also associated with fewer steps/day and more sedentary activity levels. Similar to sleep, this relationship was stronger for older adults:
- 520 fewer steps/day were taken across the entire sample by those responding “All or almost all of the time” than by those responding “None or almost none of the time” regarding loneliness.
- 1500 fewer steps/day were taken by older adults responding “All or almost all of the time”, when excluding individuals with comorbid health conditions such as osteoarthritis, cardiovascular disease, and respiratory diseases.
Key takeaways
This descriptive analysis benefitted from a large, established, diverse population willing to share their survey and wearable data. Although only preliminary analyses are presented here, this rich data source facilitates a better understanding of multidimensional SDOH, such as loneliness, that are typically difficult to characterize.
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- Marginalized groups, such as people who do not identify with a binary gender construct, also tend to experience high levels of loneliness.7 Although there were relatively few individuals identifying as non-binary in our sample (n=289), our results support the importance of determining how loneliness could influence health outcomes for this group.
- Perceived social support and loneliness may be part of mediating pathways leading to poorer overall health.
Passive collection of sleep and activity data represent new ways to explore whether our behaviors and loneliness interact with each other and contribute to negative health outcomes.
- A better understanding of the relationship between sleep and loneliness could have a significant impact on well-being, particularly for older adults.7 Missing out on even 30 minutes of sleep a day is considered clinically relevant for health outcomes.8
- Similarly, the difference in activity by self-reported loneliness could be important for health. A recent meta-analysis found a 15% decreased risk of all-cause mortality with an additional 1000 steps/day and a 7% decreased risk of cardiovascular-related mortality with an additional 500 steps/day.9
The results presented here only scratch the surface of this complex issue as well as the depth of the data being collected from nearly 140,000 survey respondents at the time of writing. However, they highlight the negative ways in which loneliness and other aspects of health interact and raise questions about these relationships, and how they differ between population sub-groups, that could be important for identifying at-risk individuals and contributing insights to help enhance the interventions in existing support programs.
Seeking a deeper understanding of your audience’s health and treatment experiences, motivations, influences, and barriers? Learn how Evidation can help.
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References
- New Surgeon General Advisory Raises Alarm about the Devastating Impact of the Epidemic of Loneliness and Isolation in the United States. May 3, 2023. U.S. Department of Health and Human Services. Available at here.
- Terracciano A, Luchetti M, Karakose S, Stephan Y, Sutin AR. Loneliness and risk of Parkinson disease. JAMA Neurol 2023. doi:10.1001/jamaneurol.2023.3382
- Nguyen NP, Kim SY, Yoo HB, Tran S. Work-family conflicts and pain interference among midlife adults: a longitudinal serial mediation via family strain and loneliness. Psychol Health 2023. doi:10.1080/08870446.2023.2259929
- Harris E. Meta-analysis: social isolation, loneliness tied to higher mortality. JAMA 2023;330(3):211. doi:10.1001/jama.2023.11958
- Lim MH, Qualter P, Ding D, Holt-Lunstad J, Mikton C, Smith BJ. Advancing loneliness and social isolation as a global health priority: taking three priority actions. Public Health Res Pract 2023;33(3):e3332320. doi:10.17061/phrpp3332320
- The Loneliness Epidemic Persists: A Post-Pandemic Look at the State of Loneliness among U.S. Adults. The Cigna Group. Available at here.
- Hajek A, König HH, Blessmann M, Grupp K. Loneliness and social isolation among transgender and gender diverse people. Healthcare (Basel). 2023;11(10):1517. doi:10.3390/healthcare11101517
- Cepeda MS, Stang P, Blacketer C, Kent JM, Wittenberg GM. Clinical relevance of sleep duration: results from a cross-sectional analysis using NHANES. J Clin Sleep Med. 2016;12(6):813-9. doi:10.5664/jcsm.5876
- Banach M, Lewek J, Surma S, Penson PE, Sahebkar A, Martin SS, Bajraktari G, Henein MY, Reiner Ž, Bielecka-Dąbrowa A, Bytyçi I, LBPMC Group and ILEP. The association between daily step count and all-cause and cardiovascular mortality: a meta-analysis, European Journal of Preventive Cardiology, 2023; zwad229. doi:10.1093/eurjpc/zwad229
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Case Studies
Unpacking the lived experience: How loneliness can affect our health
The problem
The survey and wearable data
Findings
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
Depressive and anxiety symptoms
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Activity levels
Key takeaways
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- example
- example
References
Related work
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Case Studies
Unpacking the lived experience: How loneliness can affect our health
The problem
The survey and wearable data
Findings
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
Depressive and anxiety symptoms
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Activity levels
Key takeaways
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- example
- example
References
Related work
Have questions?
Subscribe to our business newsletter
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Case Studies
Unpacking the lived experience: How loneliness can affect our health
Evidation and the Duke Big Ideas Lab have announced a partnership that aims to find ways to both increase representation of underserved populations and improve adherence among all participants in digital health studies.
The organizations are working together to build an analytic structure that will be available to other digital health researchers, helping to better predict study participation, adherence, and retention. Click below to read more about the project, led by Iredia M. Olaye, PhD, MSc, MHA, of Covered By Group and Evidation, in HealthLeaders.
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Bertina Yen, Evidation's Senior Vice President of People & Community
Bertina Yen is Evidation's Senior Vice President of People & Community, where she is responsible for the end-to-end employee experience and building a community that supports everyone's ability to show up as their authentic selves and perform their best work. Prior to joining Evidation, Bertina served as EVP overseeing clinical teams, product management, marketing, and product development at Zynx Health, driving development of evidence-based clinical decision support solutions that improve health and financial outcomes.
Bertina received her BAS from Stanford, then completed her MD and residency in internal medicine at UC San Diego. She also holds an MPH in health services administration from UCLA.
Bertina is the resident DJ at Evidation and sources the music that is played during the All-Employee Meetings. Outside of work, she enjoys hiking, traveling, and watching anything with a live audience (sporting events, plays, movies). She also starts every morning by completing at least one crossword puzzle!
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Case Studies
Unpacking the lived experience: How loneliness can affect our health
The problem
The survey and wearable data
Findings
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
Depressive and anxiety symptoms
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Activity levels
Key takeaways
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- example
- example
References
Related work
Have questions?
Subscribe to our business newsletter
Case Studies
Unpacking the lived experience: How loneliness can affect our health
The problem
The survey and wearable data
Findings
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
Depressive and anxiety symptoms
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Activity levels
Key takeaways
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- example
- example
References
Related work
Have questions?
Subscribe to our business newsletter
Case Studies
Unpacking the lived experience: How loneliness can affect our health
The problem
The survey and wearable data
Findings
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
Depressive and anxiety symptoms
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Activity levels
Key takeaways
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- example
- example
References
Related work
Have questions?
Subscribe to our business newsletter
Unpacking the lived experience: How loneliness can affect our health
October 18, 2023
Case Studies
Unpacking the lived experience: How loneliness can affect our health
October 18, 2023
Case Studies
Unpacking the lived experience: How loneliness can affect our health
October 18, 2023
Case Studies
Unpacking the lived experience: How loneliness can affect our health
October 18, 2023
Case Studies
The problem
The survey and wearable data
Findings
Age
Of those surveyed, young adults ages 18 to 25 experienced the highest levels of loneliness, with a notable decreasing trend with increasing age:
Gender
Rates of loneliness were highest among individuals who identify as non-binary:
Availability of support
People who were more frequently lonely reported receiving less help and support from their close connections:
Depressive and anxiety symptoms
Mean scores for PHQ-8 (possible range = 0-24)
3.2 for those who responded “None or almost none of the time”
12.3 for those who responded “All or almost all of the time”
Mean scores for GAD-7 (possible range = 0-21)
3.1 for those who responded “None or almost none of the time”
11.0 for those who responded “All or almost all of the time”
Sleep
Activity levels
Key takeaways
Our findings support those of other surveys regarding the trends in loneliness by age, gender, and perceived level of support.6
- example
- example
References
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