What to know
The PLACES Health-Related Social Needs data capture 7 key factors such as food and housing insecurity, transportation barriers, social isolation, and lack of health insurance, which can affect health outcomes. These data provide more comprehensive information about opportunities and barriers to health to better understand health outcomes and needs across different communities and geographic areas.
Feelings of social isolation among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who report always/usually/sometimes feeling socially isolated. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Current
Summary
Loneliness is defined as the discrepancy between a person’s desired and actual social relationships and is sometimes considered synonymous with social isolation, although they are two distinct concepts1. Loneliness is an emotional response to social isolation, while social isolation is an objective measure of the lack of social interactions and relationships1. Previous studies show that social isolation and loneliness are common sources of chronic stress in adults23, and are common at the end of life, affecting 1 in 4 older adults4. Positive relationships and interactions with family, friends, co-workers, and community members can have a protective impact on individual health and well-being, and these relationships can also help mitigate the negative impacts of challenges that people face (e.g., living in an unsafe neighborhood, trouble affording housing or food)5. Past research shows that people with high levels of social isolation6 are at higher risk of developing chronic conditions (e.g., depression, cardiovascular disease, hypertension, cancer) and have a higher risk of mortality78.
Notes
This measure used the survey question that is part of the Social Determinants and Health Equity optional module of the Behavioral Risk Factor Surveillance System. This measure is only available for states that chose to administer the module.
Related Objectives or Recommendations
None
Receipt of food stamps (past 12 months) among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who reported receiving food stamps, also called SNAP, the Supplemental Nutrition Assistance Program, on an EBT card. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Past 12 months
Summary
Food insecurity is defined as the inability to afford nutritionally adequate and safe foods9. There is a growing literature documenting relationships between food insecurity and chronic diseases101112. The Supplemental Nutrition Assistance Program (SNAP) has shown a substantial reduction in the prevalence of food insecurity and negative health outcomes13. Unmet social needs can impact health through disease outcomes, such as chronic stress, and by further impacting the ability to access needed resources14. Unmet social needs themselves may be influenced by larger structural determinants of health and may be differentially experienced by people of vulnerable population groups. Addressing both individual and population level unmet health related social needs can help reduce adverse health outcomes151617.
Notes
This measure used the survey question that is part of the Social Determinants and Health Equity optional module of the Behavioral Risk Factor Surveillance System. This measure is only available for states that chose to administer the module.
Related Objectives or Recommendations
Healthy People 2030 objective: NWS‑01. Reduce household food insecurity and hunger.
Food insecurity (past 12 months) among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who reported that the food that they bought always/usually/sometimes did not last, and they didn’t have money to get more. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Past 12 months
Summary
In 2023, around 18 million US households reported being food insecure at some time during the year18 People with low income, people with a disability, and some racial/ethnic groups are more likely to experience food insecurity181920. Limited physical access to healthy foods and transportation options in neighborhoods can also increase a person’s risk for food insecurity21. Food insecurity is associated with chronic and acute health problems and health care needs in children20, and food-insecure adults are at a higher risk of developing several chronic conditions, including coronary heart disease, diabetes, obesity, and cancer1922. Connecting individuals and families who are food insecure to food and income assistance programs can help to address food insecurity21.
Notes
This measure used the survey question that is part of the Social Determinants and Health Equity optional module of the Behavioral Risk Factor Surveillance System. This measure is only available for states that chose to administer the module.
Related Objectives or Recommendations
Healthy People 2030 objective: NWS‑01. Reduce household food insecurity and hunger.
Housing insecurity in the past 12 months among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who were not able to pay mortgage, rent, or utility bill in the past 12 months. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Past 12 months
Summary
Literature has shown that housing insecurity or instability is associated with limited access to health care23 and poor health outcomes24. Housing cost burden (spending more than 30% income on housing) is one challenge of housing instability, which also includes housing quality, overcrowding, and moving frequently2526. In 2022, 42.1 million households were cost-burdened25. People who are renters, people living in urban areas, and some racial and ethnic minority groups are more likely to experience a housing cost burden2728. Living in unaffordable housing is associated with overall poor health and increased risk of disease, including hypertension and cardiovascular disease2526. Programs that make housing more affordable for both renters and homeowners and housing subsidies that provide financial assistance to pay rent can help improve housing cost burden2528. Recent systematic reviews show that permanent supportive housing interventions increased long-term housing stability, reduced homelessness29, and improved health outcomes related to human immunodeficiency virus, anxiety, and depression among people experiencing homelessness30.
Notes
Indicator does not convey a comprehensive measure of housing instability. The indicator does not include housing and neighborhood safety, housing quality, crowding, or residential stability (moving frequently). This measure used the survey question that is part of the Social Determinants and Health Equity optional module of the Behavioral Risk Factor Surveillance System. This measure is only available for states that chose to administer the module.
Related Objectives or Recommendations
Healthy People 2030 objective: SDOH-04. Reduce the proportion of families that spend more than 30 percent of income on housing.
Utility services threat in the past 12 months among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who reported that an electric, gas, oil, or water company threatened to shut off services at any time during the prior 12 months. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Past 12 months
Summary
Unmet social needs can impact health through disease outcomes, such as chronic stress, and in further impacting the ability to access needed resources14. Unmet social needs themselves may be influenced by larger structural determinants of health and may be differentially experienced by people of vulnerable population groups. Addressing both individual and population level unmet health related social needs can help reduce adverse health outcomes151617.
Notes
This measure used the survey question that is part of the Social Determinants and Health Equity optional module of the Behavioral Risk Factor Surveillance System. This measure is only available for states that chose to administer the module.
Related Objectives or Recommendations
None
Lack of reliable transportation in the past 12 months among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who reported a lack of reliable transportation keeping them from medical appointments, meetings, work, or from getting things needed for daily living in the past 12 months. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Past 12 months
Summary
Nearly 2% of the U.S. population delayed medical care because they did not have transportation in 201731. Lack of available, convenient, or reliable transportation can affect a person’s ability to consistently access health care services, which can lead to delays in healthcare and medication use that can subsequently impact overall health3233. In addition, the inability to access reliable transportation to work, schools, and grocery stores is associated with higher rates of unemployment, poverty, and chronic illness34. People with lower incomes and uninsured people are more likely to experience transportation barriers3334. Limited public transportation infrastructure in a neighborhood leaves people without access to vehicles lacking in reliable transportation options34. Offering free or reimbursed public transit or taxi costs, connecting individuals to transportation, and policies that improve the safety and accessibility of sidewalks and bike lanes can help improve transportation access3435.
Notes
This measure used the survey question that is part of the Social Determinants and Health Equity optional module of the Behavioral Risk Factor Surveillance System. This measure is only available for states that chose to administer the module.
Related Objectives or Recommendations
None
Lack of social and emotional support among adults
Population
All Adults
Model-based measure
A multi-level regression and post-stratification approach was applied to BRFSS and ACS data to compute a detailed probability among adults who report sometimes, rarely, or never getting the social and emotional support needed. The probability was then applied to the detailed population estimates at the appropriate geographic level to generate the prevalence. The 95% confidence interval was derived using Monte Carlo simulation. Detailed methods are available here.
Measure Type
Prevalence (crude and age-adjusted)
Time Period of Case Definition
Current
Summary
Positive relationships and interactions with family, friends, co-workers, and community members can have a protective impact on individual health and well-being, and these relationships can also help mitigate the negative impacts of challenges that people face (e.g., living in an unsafe neighborhood, trouble affording housing or food)5. Past research shows that people with high levels of social isolation (lack of interactions with others or the wider community)6 are at higher risk of developing chronic conditions (e.g., depression, cardiovascular disease, hypertension) and have a higher risk of mortality7.
Notes
None
Related Objectives or Recommendations
None
- Masi CM, Chen HY, Hawkley LC, and Cacioppo JT. A meta-analysis of interventions to reduce loneliness. Pers Soc Psychol Rev 15: 219–266, 2011.
- McPherson M, Smith-Lovin L, and Brashears ME. Social isolation in America: changes in core discussion networks over two decades. Am Sociol Rev 71: 353–375, 2006.
- Steptoe A. and Kivimaki M. Stress and cardiovascular disease: an update on current knowledge. Annu Rev Public Health 34: 337–354, 2013.
- Kotwal AA, Cenzer IS, Waite LJ, et al. The epidemiology of social isolation and loneliness among older adults during the last years of life. J Am Geriatr Soc. 2021;69(11):3081-3091. doi: https://doi.org/10.1111/jgs.17366
- Healthy People 2030. Social and Community Context. U.S. Department of Health and Human Services. Accessed October 25, 2024. https://health.gov/healthypeople/objectives-and-data/browse-objectives/social-and-community-context
- Healthy People 2030. Social Cohesion. U.S. Department of Health and Human Services. Accessed October 25, 2024. https://health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/social-cohesion
- Leigh-Hunt N, Bagguley D, Bash K, Turner V, Turnbull S, Valtorta N. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health. 2017;152:157-171. doi: https://doi.org/10.1016/j.puhe.2017.07.035
- Wang F, Gao Y, Han Z, et al. A systematic review and meta-analysis of 90 cohort studies of social isolation, loneliness and mortality. Nat Hum Behav. 2023;7(8):1307-1319. doi: https://doi.org/10.1038/s41562-023-01617-6
- Anderson SA. Core indicators of nutritional state for difficult-to-sample populations. J Nutr. 1990;120 Suppl 11:1559–600.
- Laraia BA. Food insecurity and chronic disease. Adv Nutr. 2013;4:203–12. doi: https://doi.org/10.3945/an.112.003277
- Decker D, Flynn M. Food insecurity and chronic disease: addressing food access as a healthcare issue. R I Med J (2013). 2018;101:28–30.
- Weaver LJ, Fasel CB. A systematic review of the literature on the relationships between chronic diseases and food insecurity. Food Nutr Sci. 2018;09:519–41. https://doi.org/10.4236/fns.2018.95040.
- Gundersen C, Ziliak JP. Food insecurity and health outcomes. Health Aff (Millwood). 2015;34(11):1830-1839. doi: https://doi.org/10.1377/hlthaff.2015.0645
- Heller CG, Rehm CD, Parsons AH, Chambers EC, Hollingsworth NH, Fiori KP. The association between social needs and chronic conditions in a large, urban primary care population. Prev Med. 2021;153:106752. doi: https://doi.org/10.1016/j.ypmed.2021.106752
- Centers for Medicare and Medicaid Services. The Accountable Health Communities Health-Related Social Needs Screening Tool https://www.cms.gov/priorities/innovation/files/worksheets/ahcm-screeningtool.pdf. Accessed May 1, 2024.
- Billioux A, Verlander K, Anthony S, Alley D. Standardized Screening for Health-Related Social Needs in Clinical Settings: The Accountable Health Communities Screening Tool. NAM Perspectives. National Academy of Medicine. 2017 https://doi.org/10.31478/201705b
- Town M, Eke P, Zhao G, et al. Racial and ethnic differences in social determinants of health and health-related social needs among adults — Behavioral Risk Factor Surveillance System, United States, 2022. MMWR Morb Mortal Wkly Rep 2024;73:204–208. doi: https://doi.org/10.15585/mmwr.mm7309a3
- U.S. Department of Agriculture, Economic Research Service. Key Statistics & Graphics. U.S. Department of Agriculture; 2024. Updated September 4, 2024. Accessed October 25, 2024. https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics.aspx
- Hernandez DC, Reesor LM, Murillo R. Food insecurity and adult overweight/obesity: gender and race/ethnic disparities. Appetite. 2017;117:373-378. doi: https://doi.org/10.1016/j.appet.2017.07.010
- Thomas MMC, Miller DP, Morrissey TW. Food insecurity and child health. Pediatrics. 2019;144(4):e20190397. doi: https://doi.org/10.1542/peds.2019-0397
- U.S Department of Health and Human Services. Food Insecurity. Healthy People 2030. Accessed April 4, 2023. https://health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/food-insecurity
- Gregory CA, Coleman-Jensen A. Food Insecurity, Chronic Disease, and Health Among Working-Age Adults. U.S. Department of Agriculture; 2017. http://www.ers.usda.gov/publications/pub-details/?pubid=84466
- Simon AE, Fenelon A, Helms V, Lloyd PC, Rossen LM. HUD housing assistance associated with lower uninsurance rates and unmet medical need. Health Aff (Millwood). 2017;36(6):1016–1023. doi: https://doi.org/10.1377/hlthaff.2016.1152
- Angel S, Bittschi B. Housing and health. Rev Income Wealth. 2017;65(3):495–513. doi: https://doi.org/10.1111/roiw.12341
- Healthy People 2030. Housing Instability. U.S Department of Health and Human Services. Accessed April 4, 2023. https://health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/housing-instability
- Pollack CE, Griffin BA, Lynch J. Housing affordability and health among homeowners and renters. Am J Prev Med. 2010;39(6):515-21. doi: https://doi.org/10.1016/j.amepre.2010.08.002
- United States Census Bureau. Renters More Likely Than Homeowners to Spend More Than 30% of Income on Housing in Almost All Counties. United States Census Bureau; 2022. https://www.census.gov/library/stories/2022/12/housing-costs-burden.html
- Hess C, Colburn G, Crowder K, Allen R. Racial disparity in exposure to housing cost burden in the United States: 1980-2017. Hous Stud. 2022;37(10):1821-1841. doi: https://doi.org/10.1080/02673037.2020.1807473
- Aubry T, Bloch G, Brcic V, et al. Effectiveness of permanent supportive housing and income assistance interventions for homeless individuals in high-income countries: a systematic review. Lancet Public Health. 2020;5(6):e342-e360. doi: https://doi.org/10.1016/S2468-2667(20)30055-4
- Onapa H, Sharpley CF, Bitsika V, et al. The physical and mental health effects of housing homeless people: A systematic review. Health Soc Care Community. 2022;30(2):448-468. doi: https://doi.org/10.1111/hsc.13486
- Wolfe MK, McDonald NC, Holmes GM. Transportation barriers to health care in the United States: findings from the National Health Interview Survey, 1997-2017. Am J Public Health. 2020;110(6):815-822. doi: https://doi.org/10.2105/AJPH.2020.305579
- Healthy People 2030. Access to Health Services. U.S. Department of Health and Human Services. Accessed April 5, 2023. https://health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/access-health-services.
- Syed ST, Gerber BS, Sharp LK. Traveling towards disease: transportation barriers to health care access. J Community Health. 2013;38(5):976-93. doi: https://doi.org/10.1007/s10900-013-9681-1
- United States Department of Transportation. Expanding Access. United States Department of Transportation; 2022. https://www.transportation.gov/sites/dot.gov/files/2022-04/Expanding_Access.pdf
- Starbird LE, DiMaina C, Sun CA, Han HR. A systematic review of interventions to minimize transportation barriers among people with chronic diseases. J Community Health. 2019;44(2):400-411. doi: https://doi.org/10.1007/s10900-018-0572-3