Is distance associated with tuberculosis treatment outcomes? A retrospective cohort study in Kampala, Uganda

Abstract

Background: Challenges accessing nearby health facilities may be a barrier to initiating and completing tuberculosis (TB) treatment. We aimed to evaluate whether distance from residence to health facility chosen for treatment is associated with TB treatment outcomes. Methods: We conducted a retrospective cohort study of all patients initiating TB treatment at six health facilities in Kampala from 2014 to 2016. We investigated associations between distance to treating facility and unfavorable TB treatment outcomes (death, loss to follow up, or treatment failure) using multivariable Poisson regression. Results: Unfavorable treatment outcomes occurred in 20% (339/1691) of TB patients. The adjusted relative risk (aRR) for unfavorable treatment outcomes (compared to treatment success) was 0.87 (95% confidence interval [CI] 0.70, 1.07) for patients living ≥2 km from the facility compared to those living closer. When we separately compared each type of unfavorable treatment outcome to favorable outcomes, those living ≥2 km from the facility had increased risk of death (aRR 1.42 [95%CI 0.99, 2.03]) but decreased risk for loss to follow-up (aRR 0.57 [95%CI 0.41, 0.78]) than those living within 2 km. Conclusions: Distance from home residence to TB treatment facility is associated with increased risk of death but decreased risk of loss to follow up. Those who seek care further from home may have advanced disease, but once enrolled may be more likely to remain in treatment.

Geographic accessibility to health facilities predicts uptake of community-based tuberculosis screening in an urban setting

“…Our findings complement previous studies which found that reduced geographic accessibility is associated with poorer TB diagnostic indicators, adherence, and treatment outcomes ( Robsky et al, 2020 , Shargie et al, 2007 , Tripathy et al, 2013 ). Studies in Ethiopia, Malawi, and Asia found associations between reduced geographic accessibility of health facilities and both TB diagnostic delays ( Cai et al, 2015 , Tadesse et al, 2013 ) and lower case notification rates ( Bui et al, 2018 , Dangisso et al, 2015 , MacPherson et al, 2019 , Shaweno et al, 2017 ).…”

“…Our finding is consistent with other studies in urban settings in Iran and Canada that found that Euclidean distance-based measures were not well correlated with those on the basis of networks, and therefore, if possible, Euclidean distance should not be used as a proxy for geographic accessibility in place of a network distance ( Apparicio et al, 2017 , Masoodi et al, 2015 ). However, two other urban studies in Durban, South Africa, and Kampala, Uganda found little difference between Euclidean distance and network travel time as predictors of HIV virologic failure among ART users ( Chen et al, 2019 ) and TB outcomes ( Robsky et al, 2020 ), respectively. Another Canadian study in Montreal concluded that using Euclidean distance as a proxy for network distance can introduce substantial errors when considering the city periphery ( Apparicio et al, 2003 ).…”

HIV infection modifies the relationship between distance to a health facility and treatment success rate for tuberculosis in rural eastern Uganda

“…We anticipate that with a larger sample size, this finding might be significant. This result is consistent with the findings of an earlier study in Kampala, Uganda that report a trend towards increased mortality among people with TB who travel ≥2 km to receive treatment compared to those who travel <2 km [7] .…”

“…Several studies have examined other factors that influence TSR such as age, HIV status, and the category of persons with TB, residence, and sex [4] , [5] , [6] . A recent study in Uganda showed distance may negatively influence treatment success but the evidence did not reach statistical significance [7] . In Ethiopia, one study showed that TB case notification and treatment success rates were lower where there was a long-distance between a health facility and patients’ residence [8] .…”

Clinical, health systems and neighbourhood determinants of tuberculosis case fatality in urban Blantyre, Malawi: a multilevel epidemiological analysis of enhanced surveillance data

“…Our routine monitoring and evaluation show consistently very high agreement with national TB treatment registers. We additionally captured TB patients' household GPS coordinates at the point of registration for TB treatment; most previous studies have attempted to retrospectively geolocate patients' households using physical addresses, a method that is prone to error [34,35]. Our analysis of household to clinic distance was analysed at a continuous scale rather than on a transformed categorical scale with arbitrary value cut-off points [36,37].…”