Feelings of Loneliness*
About
Percentage of adults reporting that they always, usually or sometimes feel lonely. The 2025 Annual Data Release used data from 2022 for this measure.
Loneliness is a complicated emotional and social experience. Circumstances that cause one person to experience loneliness may not contribute to someone else feeling lonely.1 Loneliness is usually defined as a distressing feeling that comes from a gap between the social connection someone wants and what they have.2,3 We measure loneliness as a percentage of adults in a county that report that they always, usually or sometimes feel lonely.
Loneliness can stem from the quantity or quality of relationships.2 It can arise because an individual has fewer social contacts than they would like, or because the level of intimacy they desire in their existing relationships is not present.1 Worldviews that promote prejudice, fear or hostility toward groups of people based on their identities — such as their race or sexuality — create conditions in which people with these stigmatized identities face barriers to health. People who belong to groups that have been devalued by society may feel lonely more often and may experience a stronger negative impact on their health because of this loneliness.4 For example, bisexual and transgender individuals report some of the highest rates of loneliness.1 A 2022 study found that the prevalence of loneliness was 56.7% for bisexual individuals and ranged from 56.4% to 63.9% for transgender individuals.1 Stigma like biphobia and transphobia contribute to negative worldviews of LGBTQ+ people and could contribute to the high rates of loneliness experienced by these individuals. A lack of funding for research specific to these individuals contributes to a lack of evidence-based interventions, further marginalization and increased rates of loneliness for LGBTQ+ people.4,5
Data and methods
Data Source
Behavioral Risk Factor Surveillance System
The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based random digit dial (RDD) telephone survey that is conducted annually in all states, the District of Columbia, and United States territories. Data obtained from the BRFSS are representative of each state’s total non-institutionalized population over 18 years of age and have included more than 400,000 annual respondents with landline telephones or cellphones since 2011. Data are weighted using iterative proportional fitting (also called "raking") methods to reflect population distributions. Data from the BRFSS are used to measure various health behaviors and health-related quality of life (HRQoL) indicators in the Health Snapshots and downloadable datasets. HRQoL measures are age-adjusted to the 2000 U.S. standard population.
Prior to the 2016 Annual Data Release, up to seven survey years of landline only BRFSS data were aggregated to produce county estimates. However, even with multiple years of data, these did not provide reliable estimates for all counties, particularly those with smaller respondent samples. For the 2016 Annual Data Release and beyond, the CDC produced county estimates using single-year BRFSS data and a multilevel modeling approach based on respondent answers and their age, sex, and race/ethnicity, combined with county-level poverty, as well as county- and state-level contextual effects.1 To produce estimates for those counties where there were no or limited data, the modeling approach borrowed information from the entire BRFSS sample as well as Census Vintage population estimates. CDC used a parametric bootstrapping method to produce standard errors and confidence intervals for those point estimates. This estimation methodology was validated for all U.S. counties, including those with no or small (< 50 respondents) samples.2 This same method was used in constructing the 500 cities study, which includes BRFSS data for the 500 largest cities in the U.S.
For the 2021 Annual Data Release, the CDC has updated their modeling procedure for producing small-area estimates. With the PLACES project, a multilevel statistical modeling framework using multilevel regression and poststratification (MRP) is performed for small-area estimation that links BRFSS data with high spatial resolution population demographic and socioeconomic data from the Census’ American Community Survey (ACS). The CDC has performed internal and external validation studies, which confirm strong consistency between their model-based estimates and the direct BRFSS survey estimates at both the state and county levels. For more technical information on the PLACES modeling procedure, please see their website.3
1Zhang X, Holt JB, Lu H, Wheaton AG, Ford ES, Greenlund K, Croft JB. Multilevel regression and poststratification for small-area estimation of population health outcomes: a case study of chronic obstructive pulmonary disease prevalence using the Behavioral Risk Factor Surveillance System. American Journal of Epidemiology 2014;179(8):1025–1033.
2Zhang X, Holt JB, Yun, S, Lu H, Greenlund K, Croft JB. Validation of multilevel regression and poststratification methodology for small area estimation of health outcomes. American Journal of Epidemiology 2015;182(2):127-137.
3PLACES Project. Centers for Disease Control and Prevention. Accessed March 9, 2021. https://www.cdc.gov/places.
Website to download data
For more detailed methodological information
Key Measure Methods
Feelings of Loneliness is a percentage
Feelings of Loneliness is the percentage of adults in a county who report that they always, usually or sometimes feel lonely.
Feelings of Loneliness estimates are age-adjusted
We report an age-adjusted rate in order to fairly compare counties with differing age structures.
Feelings of Loneliness estimates are created using statistical modeling
Surveys collect information about a limited portion of a population. Statistical modeling can be used to predict how people who share certain characteristics with those surveyed may have responded to the survey. Modeling can increase the power of survey data by generating more stable estimates for places with small numbers of residents or survey responses. The Feelings of Loneliness estimates are produced from one year of survey data and are created using complex statistical modeling. For more technical information on PLACES modeling using BRFSS data, please see their methodology.
There are also drawbacks to using modeled data. The smaller the population or sample size of a county, the more the estimates are derived from the model itself and the less they are based on survey responses. Models make assumptions about statistical relationships that may not apply in all cases. Finally, there is no perfect model and each model generally has limitations specific to its methods.
Caution should be used when comparing these estimates across states
BRFSS survey data are collected independently by each state, which could result in data collection differences.
Caution should be used when comparing these estimates across years
Estimates may not be comparable across years because of methodological changes in PLACES.
Measure limitations
These data are only available for counties within states that offered the optional Social Determinants and Health Equity module of the BRFSS. Eleven states are missing these data in the 2025 Data Release including Arkansas, Colorado, Hawaii, Illinois, Louisiana, New York, North Dakota, Oregon, Pennsylvania, South Dakota and Virgina.
Numerator
The numerator is the number of respondents who answered “always,” “usually” or “sometimes” to the question: “How often do you feel lonely?”
Denominator
The denominator is the total number of adult respondents in a county.
Can This Measure Be Used to Track Progress
Modeled estimates have specific drawbacks with their usefulness in tracking progress in communities. Modeled data may not capture the effects of local conditions, such as health promotion policies. To better understand and validate modeled estimates, it is helpful to supplement estimates with additional local data.
Additionally, methodological changes may limit the ability to track progress across years using this measure. For more information on methodological changes, see above.
Finding More Data
Stratified estimates by age, gender, race/ethnicity or poverty are not available.
References
- Yanguas J, Pianazo-Henandis S, Tarazona-Santabalbina, FJ. The complexity of loneliness. Acta BioMedica. 2018;89(2):302–314.
- Hutten, E, Jongen EMM, Vos AECC, van den Hout AJHC, van Lankveld JJDM. Loneliness and mental health: The mediating effect of perceived social support. International Journal of Environmental Research and Public Health. 2021;18(22):11963.
- Bruss KV, Seth P, Zhao G. Loneliness, lack of social and emotional support, and mental health issues — United States, 2022. Morbidity and Mortality Weekly Report. 2024;73(24):539–545.
- Doyle DM, Molix L. Disparities in social health by sexual orientation and the etiologic role of self-reported discrimination. Archives of Sexual Behavior. 2016;45(6):1317–1327.
- Elmer EM, van Tilburg T, Fokkema T. Minority stress and loneliness in a global sample of sexual minority adults: The roles of social anxiety, social inhibition, and community involvement. Archives of Sexual Behavior. 2022;51(4):2269–2298.