Social Associations
About
Number of membership associations per 10,000 population. The 2025 Annual Data Release used data from 2022 for this measure.
Social isolation and loneliness have adverse effects on various health outcomes, including cardiovascular disease, cognitive impairment, depression, chronic stress, and premature mortality.1 Research suggests that the magnitude of risk associated with social isolation is similar to the risk of cigarette smoking.2 Furthermore, social support networks have been identified as powerful predictors of health behaviors, suggesting that individuals without a strong social network are less likely to make healthy lifestyle choices than individuals with a strong network. A study found that people living in areas with high levels of social trust are less likely to rate their health status as fair or poor than people living in areas with low levels of social trust.3 Researchers have argued that social trust is enhanced when people belong to voluntary groups and organizations because people who belong to such groups tend to trust others who belong to the same group.4
Data and methods
Data Source
County Business Patterns
County Business Patterns provides data on the total number of establishments, number of establishments by nine employment-size classes by detailed industry, mid-March employment, and first quarter and annual payroll for all counties in the United States and the District of Columbia.
Website to download data
For more detailed methodological information
Key Measure Methods
Social Associations is a rate
Social Associations measures the number of membership associations per 10,000 population. Rates measure the number of events in a given time period divided by the average number of people at risk during that period. Rates help us compare health data across counties with different population sizes.
Caution should be used when comparing these estimates across years
The census notes that changes in industry classification, establishment definition, and an establishment’s active status affect the comparability of the data over time. Additionally, there is no central agency or standard process among federal government agencies for assigning North American Industry Classification System (NAICS) codes to establishments and the census assigns codes based on data provided on surveys, forms, or administrative records.
Measure limitations
Data and business codes are self-reported by businesses in a county. This measure uses the primary business code of organizations, which in some cases may not align with common understanding of a civic organization.
There is not currently a reliable, national source of data for measuring social or community support at the local level. This measure does not account for important social connections offered via family support structures, informal networks, or community service organizations, all of which are important to consider when understanding the amount of social support available within a county. It also does not account for perceived support. For instance, an individual can be a member of numerous social associations, but feel they receive no social support from those organizations.
Numerator
The numerator is the total number of membership associations in a county. The membership organizations (NAICS code) in this measure include civic organizations (813410), bowling centers (713950), golf clubs (713910), fitness centers (713940), sports organizations (711211), religious organizations (813110), political organizations (813940), labor organizations (813930), business organizations (813910), and professional organizations (813920).
Denominator
The denominator is the total resident population of a county.
Can This Measure Be Used to Track Progress
This measure can be used to measure progress with some caveats. In understanding and tracking progress in social support in a community, social associations as a measure is incomplete and simply one piece of the whole picture, as described in the limitations above.
Finding More Data
Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:
- Subcounty Area
Data related to social associations from County Business Patterns can be accessed at the ZIP code level.
References
- Stokes AC, Xie W, Lundberg DJ, Glei DA, Weinstein MA. Loneliness, social isolation, and all-cause mortality in the United States. SSM – Mental Health. 2021;1(1000014).
- House JS. Social isolation kills, but how and why? Psychosomatic Medicine. 2001;63(2):273-274.
- Kawachi IK, Bruce P, Glass R. Social capital and self-rated health: A contextual analysis. American Journal of Public Health. 1999;89(8):1187-1193.
- Rupasingha A, Goetz SJ, Freshwater D. The production of social capital in U.S. counties. The Journal of Socioeconomics. 2006;35(1):83-101.