Cancer causes & control : CCC · 2026
Mammography screening in Tennessee: a tract-level spatial analysis of geographic and socioeconomic disparities.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Namin Sima, Wall Jonathan S, Heidel R Eric, Brooks Ashton, Allen Savannah, Ferris Jennifer
Аннотация
PURPOSE: Despite improvements in early detection, Tennessee ranks among the top ten states for breast cancer mortality among women. Mammography screening and early diagnosis are critical to reducing mortality, yet access and uptake vary widely across the State. We tested whether access to diagnostic services affected screening in the State.
METHODS: We merged CDC PLACES estimates of screening among women aged 50-74 with geocoded FDA-certified mammography facilities to derive drive-time categories. Tract covariates included education, poverty, insurance, race/ethnicity, primary care provider density, urban/rural status, and Appalachian designation. We mapped hot/cold spots using Getis-Ord Gi* and fit four nested beta-regression models: geography only, socioeconomic only, combined, and combined plus log-provider density.
RESULTS: Median screening prevalence was 74.8%. Hotspots clustered around Memphis, Nashville, and Knoxville; cold spots in Central Appalachian and western floodplain tracts. Geography explained ~ 23% of between-tract variation (pseudo-R2 = 0.238); socioeconomic covariates ~ 61% (0.607). In combined models, drive-time and Appalachian effects attenuated. Urban tracts screened 0.72 percentage points (pp) higher than rural, and each 1-pp rise in adults without a high-school diploma predicted - 0.13 pp.
CONCLUSION: Urbanicity and education were the primary drivers of mammography screening disparities in Tennessee. To improve early diagnosis and outcomes, interventions should prioritize educational outreach, poverty reduction, insurance expansion, and improved geographic access, via mobile units or telehealth, targeting remote cold-spot tracts.
METHODS: We merged CDC PLACES estimates of screening among women aged 50-74 with geocoded FDA-certified mammography facilities to derive drive-time categories. Tract covariates included education, poverty, insurance, race/ethnicity, primary care provider density, urban/rural status, and Appalachian designation. We mapped hot/cold spots using Getis-Ord Gi* and fit four nested beta-regression models: geography only, socioeconomic only, combined, and combined plus log-provider density.
RESULTS: Median screening prevalence was 74.8%. Hotspots clustered around Memphis, Nashville, and Knoxville; cold spots in Central Appalachian and western floodplain tracts. Geography explained ~ 23% of between-tract variation (pseudo-R2 = 0.238); socioeconomic covariates ~ 61% (0.607). In combined models, drive-time and Appalachian effects attenuated. Urban tracts screened 0.72 percentage points (pp) higher than rural, and each 1-pp rise in adults without a high-school diploma predicted - 0.13 pp.
CONCLUSION: Urbanicity and education were the primary drivers of mammography screening disparities in Tennessee. To improve early diagnosis and outcomes, interventions should prioritize educational outreach, poverty reduction, insurance expansion, and improved geographic access, via mobile units or telehealth, targeting remote cold-spot tracts.