American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025
Neighborhood Built Environment and Home Dialysis Utilization: Varying Patterns by Urbanicity-Dependent Patterns and Implications for Policy.
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.
Kim Byoungjun, Li Yiting, Lee Myeonggyun, Bae Sunjae, Blum Matthew F, Le Dustin, Coresh Josef, Charytan David M, Goldfarb David S, Segev Dorry L, Thorpe Lorna E, Grams Morgan E, McAdams-DeMarco Mara A
Аннотация
RATIONALE & OBJECTIVE: Despite national efforts, the uptake of home dialysis (peritoneal dialysis or home hemodialysis) remains low. Characteristics of the built environment may differentially impact home dialysis use.
STUDY DESIGN: Retrospective cohort study (2010-2019).
SETTING & PARTICIPANTS: 1,103,695 adults (aged≥18 years) initiating dialysis in the US Renal Data System.
EXPOSURE: We examined 3 built environment domains based on residential ZIP code: (1) medically underserved areas (MUAs), defined as neighborhoods with limited primary care access; (2) distance to the nearest dialysis facility; and (3) distribution of housing characteristics (structure and overcrowding).
OUTCOME: Uptake of home dialysis modalities at dialysis initiation.
ANALYTICAL APPROACH: We quantified associations between built environment characteristics and home dialysis initiation using multilevel logistic regression stratified by urbanicity type (urban, suburban, small-town, and rural).
RESULTS: Among adults initiating dialysis, 40.8% lived in MUAs. Across ZIP codes, the mean percentage of overcrowded housing was 4.2% (SD, 4.7%), and the percentage of detached housing was 61.1% (SD, 21.1%); mean distance to the nearest dialysis facility was 5.5km (SD, 9.1km). Living in MUAs was associated with reduced home dialysis use only in urban (OR, 0.94; 95% CI, 0.91-0.96) and suburban (OR, 0.92; 95% CI, 0.89-0.94) areas. Similarly, housing overcrowding was associated with decreased home dialysis use only in urban (OR, 0.88; 95% CI, 0.86-0.89) and suburban (OR, 0.91; 95% CI, 0.90-0.93) areas. Longer distance to a dialysis facility was the most salient neighborhood factor associated with increased home dialysis use in small towns (OR, 1.14; 95% CI, 1.12-1.16) and rural areas (OR, 1.17; 95% CI, 1.15-1.19).
LIMITATIONS: Housing characteristics were measured at the ZIP code level.
CONCLUSIONS: Built environment characteristics associated with home dialysis uptake vary by urbanicity. Policies should address built environment barriers that are specific to urbanicity level. For example, increasing the frequency of dialysate delivery schedules could address housing space constraints in urban and suburban areas, and promoting home dialysis might be more effective for patients living far from dialysis centers in small-town and rural areas.
STUDY DESIGN: Retrospective cohort study (2010-2019).
SETTING & PARTICIPANTS: 1,103,695 adults (aged≥18 years) initiating dialysis in the US Renal Data System.
EXPOSURE: We examined 3 built environment domains based on residential ZIP code: (1) medically underserved areas (MUAs), defined as neighborhoods with limited primary care access; (2) distance to the nearest dialysis facility; and (3) distribution of housing characteristics (structure and overcrowding).
OUTCOME: Uptake of home dialysis modalities at dialysis initiation.
ANALYTICAL APPROACH: We quantified associations between built environment characteristics and home dialysis initiation using multilevel logistic regression stratified by urbanicity type (urban, suburban, small-town, and rural).
RESULTS: Among adults initiating dialysis, 40.8% lived in MUAs. Across ZIP codes, the mean percentage of overcrowded housing was 4.2% (SD, 4.7%), and the percentage of detached housing was 61.1% (SD, 21.1%); mean distance to the nearest dialysis facility was 5.5km (SD, 9.1km). Living in MUAs was associated with reduced home dialysis use only in urban (OR, 0.94; 95% CI, 0.91-0.96) and suburban (OR, 0.92; 95% CI, 0.89-0.94) areas. Similarly, housing overcrowding was associated with decreased home dialysis use only in urban (OR, 0.88; 95% CI, 0.86-0.89) and suburban (OR, 0.91; 95% CI, 0.90-0.93) areas. Longer distance to a dialysis facility was the most salient neighborhood factor associated with increased home dialysis use in small towns (OR, 1.14; 95% CI, 1.12-1.16) and rural areas (OR, 1.17; 95% CI, 1.15-1.19).
LIMITATIONS: Housing characteristics were measured at the ZIP code level.
CONCLUSIONS: Built environment characteristics associated with home dialysis uptake vary by urbanicity. Policies should address built environment barriers that are specific to urbanicity level. For example, increasing the frequency of dialysate delivery schedules could address housing space constraints in urban and suburban areas, and promoting home dialysis might be more effective for patients living far from dialysis centers in small-town and rural areas.