Characterizing U.S. community well-being indices: a methodological synthesis and measurement systems perspective.
4 affiliations
- 1Department of Biostatistics, Boston University School of Public Health, MA, Boston, USA.
- 2Department of Health Law, Policy and Management, Boston University School of Public Health, MA, Boston, USA.
- 3Sharecare, Inc, Atlanta, GA, USA.
- 4Department of Biostatistics, Boston University School of Public Health, MA, Boston, USA. [email protected].
Abstract
Background
The proliferation of community well-being indices (CWBI) reflects growing recognition that both individual experiences and place-based conditions shape population health and quality of life. These indices are increasingly used to inform public health policy, community planning, and population health monitoring. However, there is substantial variation across indices in how community well-being is conceptualized, measured, and reported. Despite their expanding use, few studies have systematically compared these indices as integrated measurement systems. This study aimed to characterize and compare CWBI using a measurement systems perspective.Methods
We conducted a structured, purposive review of U.S.-based CWBI to characterize approaches using five methodological components describing domain and indicator selection, statistical estimation and weighting, construction and geographic aggregation, evaluation of measurement properties, and dissemination. Evaluation of measurement properties was characterized based on reported evidence of reliability, validity, and responsiveness. The Boston University-Sharecare Community Well-being Index (BU-SC CWBI) was included as an illustrative example.Results
Of the 315 measures identified, 11 met inclusion criteria and were characterized, along with the BU-SC CWBI. Across systems, the number of domains ranged from 2 to 10 (median 5), and the number of indicators ranged from 11 to 93 (median 43). Collectively, indices incorporated 86 distinct data sources drawn primarily from publicly available administrative and surveillance datasets; two systems also incorporated individual-level subjective measures. Although not mutually exclusive, systems were heuristically classified into three broad methodological orientations that reflect a continuum of priorities with respect to conceptual organization, aggregation approaches, and the use of empirical and model-based methods. Substantial heterogeneity was observed in statistical estimation, weighting, and evaluation of measurement properties, with limited and inconsistent reporting of reliability, validity, and related evaluation analyses.Conclusions
CWBI differ in both indicators used to represent well-being and methodological approaches used to construct and evaluate them. Conceptualizing these indices as measurement systems provides a structured approach for comparing approaches, clarifying trade-offs, and improving interpretability and comparability. While CWBI may be designed for different goals and applied in different contexts, a systematic approach to their characterization may facilitate transparency and more informed use in research and policy.
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BibTeX
@article{alperen2026characterizing,
title = {{Characterizing U.S. community well-being indices: a methodological synthesis and measurement systems perspective.}},
author = {Julie K Alperen and Michael LaValley and Pengsheng Ni and Tara Tripp and Danielle Emig and Prasad Patil and Shariq Mohammed and Abhi Jain and Michael Rickles and Elizabeth Colyer and Brandeus Davis and Lisa M Sullivan and Michael Acker and Kimberly A Dukes},
journal = {Population health metrics},
year = {2026},
month = jul,
doi = {10.1186/s12963-026-00502-4},
url = {https://europepmc.org/article/MED/42894172},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Characterizing U.S. community well-being indices: a methodological synthesis and measurement systems perspective.
AU - Julie K Alperen
AU - Michael LaValley
AU - Pengsheng Ni
AU - Tara Tripp
AU - Danielle Emig
AU - Prasad Patil
AU - Shariq Mohammed
AU - Abhi Jain
AU - Michael Rickles
AU - Elizabeth Colyer
AU - Brandeus Davis
AU - Lisa M Sullivan
AU - Michael Acker
AU - Kimberly A Dukes
PY - 2026
DA - 2026/07/01
JO - Population health metrics
DO - 10.1186/s12963-026-00502-4
UR - https://europepmc.org/article/MED/42894172
AB - Background The proliferation of community well-being indices (CWBI) reflects growing recognition that both individual experiences and place-based conditions shape population health and quality of life. These indices are increasingly used to inform public health policy, community planning, and population health monitoring. However, there is substantial variation across indices in how community well-being is conceptualized, measured, and reported. Despite their expanding use, few studies have systematically compared these indices as integrated measurement systems. This study aimed to characterize and compare CWBI using a measurement systems perspective.Methods We conducted a structured, purposive review of U.S.-based CWBI to characterize approaches using five methodological components describing domain and indicator selection, statistical estimation and weighting, construction and geographic aggregation, evaluation of measurement properties, and dissemination. Evaluation of measurement properties was characterized based on reported evidence of reliability, validity, and responsiveness. The Boston University-Sharecare Community Well-being Index (BU-SC CWBI) was included as an illustrative example.Results Of the 315 measures identified, 11 met inclusion criteria and were characterized, along with the BU-SC CWBI. Across systems, the number of domains ranged from 2 to 10 (median 5), and the number of indicators ranged from 11 to 93 (median 43). Collectively, indices incorporated 86 distinct data sources drawn primarily from publicly available administrative and surveillance datasets; two systems also incorporated individual-level subjective measures. Although not mutually exclusive, systems were heuristically classified into three broad methodological orientations that reflect a continuum of priorities with respect to conceptual organization, aggregation approaches, and the use of empirical and model-based methods. Substantial heterogeneity was observed in statistical estimation, weighting, and evaluation of measurement properties, with limited and inconsistent reporting of reliability, validity, and related evaluation analyses.Conclusions CWBI differ in both indicators used to represent well-being and methodological approaches used to construct and evaluate them. Conceptualizing these indices as measurement systems provides a structured approach for comparing approaches, clarifying trade-offs, and improving interpretability and comparability. While CWBI may be designed for different goals and applied in different contexts, a systematic approach to their characterization may facilitate transparency and more informed use in research and policy.
SN - 1478-7954
ER -