{"doi":"10.1007/s11524-025-01023-5","title":"Within-City Average Life Expectancy “Gaps”: A Useful Health Equity Metric","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>We characterize within-city life expectancy gaps and their correlation with social and environmental characteristics in 948 US cities. Life expectancy estimates were drawn from the US Life Expectancy Estimation Program. City life expectancy gaps were calculated by subtracting the lowest tract-level life expectancy estimate from the highest for each city. Correlations were established using Spearman’s correlation coefficient. The average city-level life expectancy gap in our sample was 11.8 years. Life expectancy gaps were larger in cities with lower average life expectancy and were evident across the USA. Life expectancy gaps of a decade were seen even in smaller cities and in high life expectancy cities. Life expectancy gaps were most strongly correlated with racialized residential segregation, children in poverty, and household income. Significant between-neighborhood gaps in life expectancy exist across US cities. Life expectancy gaps present a compelling target for establishing robust health equity goals.</jats:p>","journal":"Journal of Urban Health","year":2026,"id":617037,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":1,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":355242,"name":"Isabel S. Nelson","orcid":"0000-0001-5110-2603","position":1,"is_corresponding":false},{"id":1107612,"name":"Matthew Lee","orcid":"0000-0002-9700-8951","position":2,"is_corresponding":false},{"id":1591067,"name":"Anne Vierse","orcid":null,"position":3,"is_corresponding":false},{"id":572470,"name":"Alexander S. Chen","orcid":"0000-0002-3040-2786","position":4,"is_corresponding":false},{"id":381159,"name":"Andrea R. Titus","orcid":"0000-0001-7586-643X","position":5,"is_corresponding":false},{"id":389936,"name":"Lorna E. Thorpe","orcid":"0000-0002-5535-2674","position":6,"is_corresponding":false},{"id":969503,"name":"Marc N. Gourevitch","orcid":"0000-0001-6865-2126","position":7,"is_corresponding":false},{"id":969500,"name":"Ben R. Spoer","orcid":"0000-0002-0311-7963","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Within-City Average Life Expectancy “Gaps”: A Useful Health Equity Metric","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>We characterize within-city life expectancy gaps and their correlation with social and environmental characteristics in 948 US cities. Life expectancy estimates were drawn from the US Life Expectancy Estimation Program. City life expectancy gaps were calculated by subtracting the lowest tract-level life expectancy estimate from the highest for each city. Correlations were established using Spearman’s correlation coefficient. The average city-level life expectancy gap in our sample was 11.8 years. Life expectancy gaps were larger in cities with lower average life expectancy and were evident across the USA. Life expectancy gaps of a decade were seen even in smaller cities and in high life expectancy cities. Life expectancy gaps were most strongly correlated with racialized residential segregation, children in poverty, and household income. Significant between-neighborhood gaps in life expectancy exist across US cities. Life expectancy gaps present a compelling target for establishing robust health equity goals.</jats:p>","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"41586991","pmcid":"PMC13136456","openalex_id":"https://openalex.org/W7125712225","authors":[],"funders":[],"total_grants":0,"fwci":13.6538,"citation_percentile":0.95743675,"influential_citations":0,"citation_trend":[{"year":2026,"count":1}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://link.springer.com/content/pdf/10.1007/s11524-025-01023-5.pdf","host_type":"journal"},{"url":"https://link.springer.com/content/pdf/10.1007/s11524-025-01023-5.pdf","host_type":"publisher"},{"url":"https://link.springer.com/article/10.1007/s11524-025-01023-5","host_type":"publisher"},{"url":"https://doi.org/10.1007/s11524-025-01023-5","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/41586991","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13136456/","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC13136456","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC13136456?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Health disparities and outcomes","Global Health Care Issues","Insurance, Mortality, Demography, Risk Management","Humans","Life Expectancy","United States","Health Equity","Cities","Socioeconomic Disparities in Health","Residential Segregation","Poverty","Socioeconomic Factors","Neighborhood Characteristics"],"mesh_terms":["Health Equity","Neighborhood Characteristics","Socioeconomic Disparities in Health","Residential Segregation","Adult","Aged","Cities","Female","Humans","Life Expectancy","Male","Middle Aged","Poverty","Socioeconomic Factors","United States","Urban Population","Health Status Disparities"],"keywords":["Life expectancy","Expectancy theory","Equity (law)","Sample (material)","Estimation","Metric (unit)"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"No poverty"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"gen"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-03T00:40:52.628769Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}