Salma Shariff-Marco1, Mindy C DeRouen2, Juan Yang3, Jennifer Jain3, David O Nelson4, Margaret M Weden5, Scarlett L Gomez6. 1. Department of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA. Electronic address: salma.shariff-marco@ucsf.edu. 2. Department of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA. 3. Department of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA. 4. Cancer Prevention Institute of California, Fremont, CA. 5. RAND Corporation, Santa Monica, CA. 6. Department of Epidemiology & Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA; UCSF Helen Diller Family Comprehensive Cancer Center, San Francisco, CA; Greater Bay Area Cancer Registry, San Francisco, CA.
Abstract
PURPOSE: Previous studies on neighborhoods and breast cancer survival examined neighborhood variables as unidimensional measures (e.g. walkability or deprivation) individually and thus cannot inform how the multitude of highly correlated neighborhood domains interact to impact breast cancer survival. Neighborhood archetypes were developed that consider interactions among a broad range of neighborhood social and built environment attributes and examine their associations with breast cancer survival. METHODS: Archetypes were measured using latent class analysis (LCA) fit to California census tract-level data. Thirty-nine social and built environment attributes relevant to eight neighborhood domains (socioeconomic status (SES), urbanicity, demographics, housing, land use, commuting and traffic, residential mobility, and food environment) were included. The archetypes were linked to cancer registry data on breast cancer cases (diagnosed 1996-2005 with follow-up through Dec 31, 2017) to evaluate their associations with overall and breast cancer-specific survival using Cox proportional hazards models. Analyses were stratified by race/ethnicity. RESULTS: California neighborhoods were best described by nine archetypal patterns that were differentially associated with overall and breast cancer-specific survival. The lowest risk of overall death was observed in the upper middle class suburb (reference) and high status neighborhoods, while the highest was observed among inner city residents with a 39% greater risk of death (95% CI = 1.35 to 1.44). Results were similar for breast cancer-specific survival. Stratified analyses indicated that differences in survival by neighborhood archetypes varied according to individuals' race/ethnicity. CONCLUSIONS: By describing neighborhood archetypes that differentiate survival following breast cancer diagnosis, the study provides direction for policy and clinical practice addressing contextually-rooted social determinants of health including SES, unhealthy food environments, and greenspace.
PURPOSE: Previous studies on neighborhoods and breast cancer survival examined neighborhood variables as unidimensional measures (e.g. walkability or deprivation) individually and thus cannot inform how the multitude of highly correlated neighborhood domains interact to impact breast cancer survival. Neighborhood archetypes were developed that consider interactions among a broad range of neighborhood social and built environment attributes and examine their associations with breast cancer survival. METHODS: Archetypes were measured using latent class analysis (LCA) fit to California census tract-level data. Thirty-nine social and built environment attributes relevant to eight neighborhood domains (socioeconomic status (SES), urbanicity, demographics, housing, land use, commuting and traffic, residential mobility, and food environment) were included. The archetypes were linked to cancer registry data on breast cancer cases (diagnosed 1996-2005 with follow-up through Dec 31, 2017) to evaluate their associations with overall and breast cancer-specific survival using Cox proportional hazards models. Analyses were stratified by race/ethnicity. RESULTS: California neighborhoods were best described by nine archetypal patterns that were differentially associated with overall and breast cancer-specific survival. The lowest risk of overall death was observed in the upper middle class suburb (reference) and high status neighborhoods, while the highest was observed among inner city residents with a 39% greater risk of death (95% CI = 1.35 to 1.44). Results were similar for breast cancer-specific survival. Stratified analyses indicated that differences in survival by neighborhood archetypes varied according to individuals' race/ethnicity. CONCLUSIONS: By describing neighborhood archetypes that differentiate survival following breast cancer diagnosis, the study provides direction for policy and clinical practice addressing contextually-rooted social determinants of health including SES, unhealthy food environments, and greenspace.
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