Backgrounds The geographic disparity of prevalence rates among dialysis patients is unclear. We evaluate the association between travel time to dialysis facilities and prevalence rates of dialysis patients living in 1,867 census areas of Hiroshima, Japan. Furthermore, we study the effects of geographic features (mainland or island) on the prevalence rates and assess if these effects modify the association between travel time and prevalence. Methods The study subjects were all 7,374 people that were certified as the “renal disabled” by local governments in 2011. The travel time from each patient to the nearest available dialysis facility was calculated by incorporating both travel time and the capacity of all 98 facilities. The effect of travel time on the age- and sex-adjusted standard prevalence rate (SPR) and 95% confidence intervals (CIs) at each census area was evaluated in two-level Poisson regression models with 1,867 census areas (level 1) nested within 35 towns or cities (level 2). The results were adjusted for area-based parameters of socioeconomic status, urbanity, and land type. Furthermore, the SPR of dialysis patients was calculated in each specific subgroup of population for travel time, land type, and combination of land type and travel time. Results In the regression analysis, SPR decreased by 5.2% (95% CI: ？7.9–？2.3) per 10-min increase in travel time even after adjusting for potential confounders. The effect of travel time on prevalence was different in the mainland and island groups. There was no travel time-dependent SPR disparity on the islands. The SPR among remote residents (>30 min from facilities) in the mainland was lower (0.77, 95% CI: 0.71–0.85) than that of closer residents (≤30 min; 0.95, 95% CI: 0.92–0.97). Conclusions The prevalence of dialysis patients was lower among remote residents. Geographic difficulties for commuting seem to decrease the prevalence rate.
Maheswaran R, Payne N, Meechan D, Burden RP, Fryers PR, et al. (2003) Socioeconomic deprivation, travel distance, and renal replacement therapy in the Trent Region, United Kingdom 2000: an ecological study. J Epidemiol Community Health 57: 523–524.
Udayaraj UP, Ben-Shlomo Y, Roderick P, Casula A, Ansell D, et al. (2010) Socio-economic status, ethnicity and geographical variations in acceptance rates for renal replacement therapy in England and Wales: an ecological study. J Epidemiol Community Health 64: 535–541.
Roderick P, Clements S, Stone N, Martin D, Diamond I (1999) What determines geographical variation in rates of acceptance onto renal replacement therapy in England? J Health Serv Res Policy 4: 139–146.
Arbor Research Collaborative for Health 2010 Annual Report of the Dialysis Outcomes and Practice Patterns Study: Hemodialysis Data 1999–2008. Available: http://www.dopps.org/annualreport/index.？htm. Accessed 2012 March 1.
Matsumoto M, Ogawa T, Kashima S, Takeuchi K (2012) The impact of rural hospital closures on equity of commuting time for haemodialysis patients: simulation analysis using the capacity-distance model. Int J Health Geogr 11: 28.
Ministry of Internal Affairs and Communications Japan standard Industrial Classiffication (Rev. 12, November 2007). Available: http://www.stat.go.jp/english/data/kokus？ei/2000/terms.htm. Accessed 2012 June 24.
Moist LM, Bragg-Gresham JL, Pisoni RL, Saran R, Akiba T, et al. (2008) Travel time to dialysis as a predictor of health-related quality of life, adherence, and mortality: the Dialysis Outcomes and Practice Patterns Study (DOPPS). Am J Kidney Dis 51: 641–650.
Tonelli M, Manns B, Culleton B, Klarenbach S, Hemmelgarn B, et al. (2007) Association between proximity to the attending nephrologist and mortality among patients receiving hemodialysis. CMAJ 177: 1039–1044.
Sugisawa H, Shimizu Y, Kumagai T, Oohira S, Sugisaki H, et al. (2010) [Differences in attitudes toward care between hemodialysis patients and their family]. The Journal of Japanese Association of Dialysis Physicians 25: 135–147.
Untas A, Thumma J, Rascle N, Rayner H, Mapes D, et al. (2011) The associations of social support and other psychosocial factors with mortality and quality of life in the dialysis outcomes and practice patterns study. Clin J Am Soc Nephrol 6: 142–152.