The impact of travel time on geographic distribution of dialysis patients.
BACKGROUND
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.
Department of Public Health and Health Policy, Hiroshima University Institute of Biomedical and Health Sciences, Hiroshima, Japan. saori_ksm@ybb.ne.jp
Saori
S
Kashima
Masatoshi
M
Matsumoto
Takahiko
T
Ogawa
Akira
A
Eboshida
Keisuke
K
Takeuchi
D000293:Adolescent; D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D003710:Demography; D005260:Female; D005843:Geography; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007564:Japan; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D006435:Renal Dialysis / Q000706:statistics & numerical data; D013997:Time Factors; D014186:Transportation; D014195:Travel; D055815:Young Adult