Top

Published in:

Open Access 01-12-2021 | Tuberculosis | Research

Impact of socio-economic factors on Tuberculosis treatment outcomes in north-eastern Uganda: a mixed methods study

Authors: Jasper Nidoi, Winters Muttamba, Simon Walusimbi, Joseph F. Imoko, Peter Lochoro, Jerry Ictho, Levicatus Mugenyi, Rogers Sekibira, Stavia Turyahabwe, Raymond Byaruhanga, Giovanni Putoto, Simone Villa, Mario C. Raviglione, Bruce Kirenga

Published in: BMC Public Health | Issue 1/2021

Abstract

Background

Tuberculosis (TB) is a major public health problem and at 48%, Karamoja in North-Eastern Uganda has the lowest treatment success rate nationally. Addressing the social determinants of TB is crucial to ending TB. This study sought to understand the extent and ways in which socio-economic factors affect TB treatment outcomes in Karamoja.

Methods

We conducted a convergent parallel mixed methods study in 10 TB Diagnostic and Treatment Units. The study enrolled former TB patients diagnosed with drug-susceptible TB between April 2018 and March 2019. Unit TB and laboratory registers were reviewed to identify pre-treatment losses to follow-up. Four focus group discussions with former TB patients and 18 key informant interviews with healthcare workers were conducted. Principle component analysis was used to generate wealth quintiles that were compared to treatment outcomes using the proportion test. The association between sociodemographic characteristics and TB treatment outcomes was evaluated using the chi-square test and multiple logistic regression.

Results

A total of 313 participants were randomly selected from 1184 former TB patients recorded in the unit TB registers. Of these, 264 were contacted in the community and consented to join the study: 57% were male and 156 (59.1%) participants had unsuccessful treatment outcomes. The wealthiest quintile had a 58% reduction in the risk of having an unsuccessful treatment outcome (adj OR = 0.42, 95% CI 0.18–0.99, p = 0.047). People who were employed in the informal sector (adj OR = 4.71, 95% CI 1.18–18.89, p = 0.029) and children under the age of 15 years who were not in school or employed (adj OR = 2.71, 95% CI 1.11–6.62, p = 0.029) had significantly higher odds of unsuccessful treatment outcome. Analysis of the pre-treatment loss to follow-up showed that 17.2% of patients with pulmonary bacteriologically confirmed TB did not initiate treatment with a higher proportion among females (21.7%) than males (13.5%). Inadequate food, belonging to migratory communities, stigma, lack of social protection, drug stock-outs and transport challenges affected TB treatment outcomes.

Conclusions

This study confirmed that low socio-economic status is associated with poor TB treatment outcomes emphasizing the need for multi- and cross-sectoral approaches and socio-economic enablers to optimise TB care.

Available only for authorised users

World Health Organization. Global Tuberculosis Report. Geneva. 2020:2020.

Kyu HH, Maddison ER, Henry NJ, Mumford JE, Barber R, Shields C, et al. The global burden of tuberculosis: results from the global burden of disease study 2015. Lancet Infect Dis. 2018 Mar 1;18(3):261–84. https://doi.org/10.1016/S1473-3099(17)30703-X.CrossRef

Wingfield T, Tovar MA, Huff D, Boccia D, Saunders MJ, Datta S, et al. Beyond pills and tests: addressing the social determinants of tuberculosis. Clin Med (Northfield Il). 2016;16(Suppl 6):s79.CrossRef

World Health Organization. The End TB Strategy. World Health Organization. Geneva: World Health Organization; 2015.

Pedrazzoli D, Boccia D, Dodd PJ, Lönnroth K, Dowdy DW, Siroka A, et al. Modelling the social and structural determinants of tuberculosis: opportunities and challenges. Int J Tuberc Lung Dis. 2017;21(9):957–64. https://doi.org/10.5588/ijtld.16.0906.CrossRefPubMedPubMedCentral

Lönnroth K, Jaramillo E, Williams BG, Dye C, Raviglione M. Drivers of tuberculosis epidemics: the role of risk factors and social determinants. Soc Sci Med. 2009;68(12):2240–6. https://doi.org/10.1016/j.socscimed.2009.03.041.CrossRefPubMed

About the Sustainable Development Goals – United Nations Sustainable Development Goals [Internet]. Available from: https://www.un.org/sustainabledevelopment/sustainable-development-goals/

Lönnroth K, Raviglione M. The WHO’s new end TB strategy in the post-2015 era of the sustainable development goals. Trans R Soc Trop Med Hyg. 2016;110(3):148–50. https://doi.org/10.1093/trstmh/trv108.CrossRefPubMedPubMedCentral

Fitchett JR, Macpherson P, Corbett EL. Implementing the end TB strategy and the intersection with the sustainable development goals, 2016-2030 challenges to ending TB. Trans R Soc Trop Med Hyg. 2016 Mar 1;110(3):145–7. https://doi.org/10.1093/trstmh/trw010.CrossRefPubMed

10.

Valles SA. A pluralistic and socially responsible philosophy of epidemiology field should actively engage with social determinants of health and health disparities. Synthese. 2019 Mar;5:1–23.

11.

Trauer JM, Dodd PJ, Gomes MGM, Gomez GB, Houben RMGJ, McBryde ES, et al. The importance of heterogeneity to the epidemiology of tuberculosis. Clin Infect Dis. 2019;69(1):159–66. https://doi.org/10.1093/cid/ciy938.CrossRefPubMed

12.

World Health Organization. WHO | Global tuberculosis report. World Health Organization. World Health Organization. 2019;2019.

13.

Solar O, Irwin A. A conceptual framework for action on the social determinants of health. Social Determinants of Health Discussion Paper 2 (Policy and Practice). Geneva. 2010.

14.

Hargreaves JR, Boccia D, Evans CA, Adato M, Petticrew M, Porter JDH. The social determinants of tuberculosis: from evidence to action. Am J Public Health. 2011;101(4):654–62. https://doi.org/10.2105/AJPH.2010.199505.CrossRefPubMedPubMedCentral

15.

Alene KA, Viney K, Gray DJ, McBryde ES, Wagnew M, Clements ACA. Mapping tuberculosis treatment outcomes in Ethiopia. BMC Infect Dis. 2019 Dec 28;19(1):474. https://doi.org/10.1186/s12879-019-4099-8.CrossRefPubMedPubMedCentral

16.

Zhang T, Tang S, Jun G, Whitehead M. Persistent problems of access to appropriate, affordable TB services in rural China: experiences of different socio-economic groups. BMC Public Health. 2007;7(1):19. https://doi.org/10.1186/1471-2458-7-19.CrossRefPubMedPubMedCentral

17.

Di Gennaro F, Pizzol D, Cebola B, Stubbs B, Monno L, Saracino A, et al. Social determinants of therapy failure and multi drug resistance among people with tuberculosis: A review. Vol. 103, Tuberculosis. Churchill Livingstone; 2017. p. 44–51, DOI: https://doi.org/10.1016/j.tube.2017.01.002.

18.

Aibana O, Slavuckij A, Bachmaha M, Krasiuk V, Rybak N, Flanigan TP, et al. Patient predictors of poor drug sensitive tuberculosis treatment outcomes in Kyiv Oblast, Ukraine. F1000Research. 2019 Nov;22(6):1873.CrossRef

19.

Rashak HA, Sánchez-Pérez HJ, Abdelbary BE, Bencomo-Alerm A, Enriquez-Ríos N, Gómez-Velasco A, et al. Diabetes, undernutrition, migration and indigenous communities: Tuberculosis in Chiapas. Mexico Epidemiol Infect. 2019;147.

20.

Secretary of Jan Swasthya Sahyog, Laux TS, Patil S. Predictors of tuberculosis treatment outcomes among a retrospective cohort in rural, Central India. J Clin Tuberc Other Mycobact Dis. 2018 Aug 1;12:41–7.CrossRef

21.

Adamu AL, Aliyu MH, Galadanci NA, Musa BM, Lawan UM, Bashir U, et al. The impact of rural residence and HIV infection on poor tuberculosis treatment outcomes in a large urban hospital: a retrospective cohort analysis. Int J Equity Health. 2018 Jan;8(1):17(1). https://doi.org/10.1186/s12939-017-0714-8.CrossRef

22.

Gelmanova IY, Keshavjee S, Golubchikova VT, Berezina VI, Strelis AK, Yanova GV, et al. Barriers to successful tuberculosis treatment in Tomsk, Russian Federation: non-adherence, default and the acquisition of multidrug resistance. Bull World Health Organ. 2007 Sep;85(9):703–11. https://doi.org/10.2471/BLT.06.038331.CrossRefPubMedPubMedCentral

23.

24.

Eshetie S, Gizachew M, Alebel A, van Soolingen D. Tuberculosis treatment outcomes in Ethiopia from 2003 to 2016, and impact of HIV co-infection and prior drug exposure: A systematic review and meta-analysis. Subbian S, editor. PLoS One. 2018 Mar 19;13(3):e0194675.

25.

Tweya H, Feldacker C, Phiri S, Ben-Smith A, Fenner L, Jahn A, et al. Comparison of Treatment Outcomes of New Smear-Positive Pulmonary Tuberculosis Patients by HIV and Antiretroviral Status in a TB/HIV Clinic, Malawi. Ho W, editor. PLoS One. 2013 Feb 15;8(2):e56248.

26.

Nglazi MD, Bekker LG, Wood R, Kaplan R. The impact of HIV status and antiretroviral treatment on TB treatment outcomes of new tuberculosis patients attending co-located TB and ART services in South Africa: a retrospective cohort study. BMC Infect Dis. 2015 Nov 19;15(1):536. https://doi.org/10.1186/s12879-015-1275-3.CrossRefPubMedPubMedCentral

27.

Ahmad Khan F, Minion J, Al-Motairi A, Benedetti A, Harries AD, Menzies D. An updated systematic review and meta-analysis on the treatment of active tuberculosis in patients with hiv infection. Vol. 55, Clinical Infectious Diseases. Clin Infect Dis; 2012. p. 1154–1163, An Updated Systematic Review and Meta-analysis on the Treatment of Active Tuberculosis in Patients With HIV Infection, 8, DOI: https://doi.org/10.1093/cid/cis630.

28.

García-Basteiro AL, Respeito D, Augusto OJ, López-Varela E, Sacoor C, Sequera VG, et al. Poor tuberculosis treatment outcomes in southern Mozambique (2011-2012). BMC Infect Dis. 2016 May;20:16(1).

29.

Koomen LEM, Burger R, Van Doorslaer EKA. Effects and determinants of tuberculosis drug stockouts in South Africa. BMC Health Serv Res. 2019 Apr 3;19(1):213. https://doi.org/10.1186/s12913-019-3972-x.CrossRefPubMedPubMedCentral

30.

Carter DJ, Glaziou P, Lönnroth K, Siroka A, Floyd K, Weil D, et al. The impact of social protection and poverty elimination on global tuberculosis incidence: a statistical modelling analysis of sustainable development goal 1. Lancet Glob Heal. 2018;6(5):e514–22. https://doi.org/10.1016/S2214-109X(18)30195-5.CrossRef

31.

Durovni B, Saraceni V, Puppin MS, Tassinari W, Cruz OG, Cavalcante S, et al. The impact of the Brazilian family health strategy and the conditional cash transfer on tuberculosis treatment outcomes in Rio de Janeiro: an individual-level analysis of secondary data. J Public Health (Oxf). 2018;40(3):e359–66. https://doi.org/10.1093/pubmed/fdx132.CrossRef

32.

Ukwaja KN, Alobu I, Gidado M, Onazi O, Oshi DC. Economic support intervention improves tuberculosis treatment outcomes in rural Nigeria. Int J Tuberc Lung Dis. 2017 May 1;21(5):564–70. https://doi.org/10.5588/ijtld.16.0741.CrossRefPubMed

33.

de Andrade KVF, Nery JS, de Souza RA, Pereira SM. Effects of social protection on tuberculosis treatment outcomes in low or middle-income and in high-burden countries: systematic review and meta-analysis. In: Effects of social protection on tuberculosis treatment outcomes in low or middle-income and in high-burden countries: systematic review and meta-analysis, vol. 34. Fundacao Oswaldo Cruz: Cadernos de Saude Publica; 2018.

34.

Lutge E, Lewin S, Volmink J, Friedman I, Lombard C. Economic support to improve tuberculosis treatment outcomes in South Africa: a pragmatic cluster-randomized controlled trial. Trials. 2013 May 28;14(1):1–13. https://doi.org/10.1186/1745-6215-14-154.CrossRef

35.

Uganda Ministry of Health. The Uganda National Tuberculosis Prevalence Survey. Survey Report. 2014-2015:2015.

36.

National Tuberculosis and Leprosy Division. National Tuberculosis And Leprosy Division: July 2017 – June 2018 Report. Uganda Ministry of Health 2018.

37.

Uganda Bureau of Statistics (UBOS). Uganda National Household Survey 2016/2017. Kampala, Uganda; 2018.

38.

Uganda Bureau of Statistics (UBOS), ICF. Uganda Demographic and Health Survey 2016. Kampala, Uganda and Rockville, Maryland, USA: UBOS and ICF; 2018.

39.

Kröger H, Pakpahan E, Hoffmann R. What causes health inequality? A systematic review on the relative importance of social causation and health selection. Eur J Pub Health. 2015;25(6):951–60. https://doi.org/10.1093/eurpub/ckv111.CrossRef

40.

Shavers VL. Measurement of socioeconomic status in health disparities research. J Natl Med Assoc. 2007 Sep;99(9):1013–23.PubMedPubMedCentral

41.

Edmonds WA, Kennedy TD. An Applied Guide to Research Designs: Quantitative, Qualitative, and Mixed Methods. Second Edi. An Applied Guide to Research Designs: Quantitative, Qualitative, and Mixed Methods. 2017. 181–188 p.

42.

Ministry of Health Uganda. Uganda eHMIS [Internet]. [cited 2020 Jan 24]. Available from: https://hmis.health.go.ug/dhis-web-commons/security/login.action

43.

Guest G, Bunce A, Johnson L. How many interviews are enough? Field methods. 2006 Feb 21;18(1):59–82. https://doi.org/10.1177/1525822X05279903.CrossRef

44.

Kootbodien T, Wilson K, Tlotleng N, Ntlebi V, Made F, Rees D, et al. Tuberculosis mortality by occupation in South Africa, 2011–2015. Int J Environ Res Public Health. 2018 Dec 1;15(12):2011–5. https://doi.org/10.3390/ijerph15122756.CrossRef

45.

Gebreweld FH, Kifle MM, Gebremicheal FE, Simel LL, Gezae MM, Ghebreyesus SS, et al. Factors influencing adherence to tuberculosis treatment in Asmara. Eritrea: A qualitative study J Heal Popul Nutr. 2018 Jan;5(1):37(1). https://doi.org/10.1186/s41043-017-0132-y.CrossRef

46.

Marahatta SB, Yadav RK, Giri D, Lama S, Rijal KR, Mishra SR, et al. Barriers in the access, diagnosis and treatment completion for tuberculosis patients in central and western Nepal: A qualitative study among patients, community members and health care workers. PLoS One. 2020;15(1).

47.

Da Silva RD, De Luna FDT, De Araújo AJ, Camêlo ELS, Bertolozzi MR, Hino P, et al. Patients’ perception regarding the influence of individual and social vulnerabilities on the adherence to tuberculosis treatment: a qualitative study. BMC Public Health. 2017 Sep;19(1):17(1). https://doi.org/10.1186/s12889-017-4752-3.CrossRef

48.

Muttamba W, Tumwebaze R, Mugenyi L, Batte C, Sekibira R, Nkolo A, et al. Households experiencing catastrophic costs due to tuberculosis in Uganda: magnitude and cost drivers. BMC Public Health. 2020;20(1):1–10. https://doi.org/10.1186/s12889-020-09524-5.CrossRef

49.

Grede N, Claros JM, Pee S de, Bloem M. Is There a Need to Mitigate the Social and Financial Consequences of Tuberculosis at the Individual and Household Level? AIDS Behav 2014 185. 2014 Apr 8;18(5):542–553.

50.

Walcott RL, Ingels JB, Corso PS, Zalwango S, Whalen CC, Sekandi JN. There’s no such thing as a free TB diagnosis: catastrophic TB costs in urban Uganda. Glob Public Health. 2020;15(6):877–88. https://doi.org/10.1080/17441692.2020.1724313.CrossRefPubMedPubMedCentral

51.

Duarte R, Lönnroth K, Carvalho C, Lima F, Carvalho ACC, Muñoz-Torrico M, et al. Tuberculosis, social determinants and co-morbidities (including HIV). Pulmonology. 2018;24(2):115–9. https://doi.org/10.1016/j.rppnen.2017.11.003.CrossRefPubMed

52.

Jackson S, Sleigh AC, Wang G-J, Liu X-L. Poverty and the economic effects of TB in rural China.

53.

Ukwaja KN, Modebe O, Igwenyi C, Alobu I. The economic burden of tuberculosis care for patients and households in Africa: A systematic review. Vol. 16, Int J Tuberculosis and Lung Disease. 2012. p. 733–739.

54.

Kamolratanakul P, Sawert H, Kongsin S, Lertmaharit S, Sriwongsa J, Na-Songkhla S, et al. Economic impact of tuberculosis at the household level. Int J Tuberc Lung Dis. 1999;3(7):596–602.PubMed

55.

Wingfield T, Boccia D, Tovar M, Gavino A, Zevallos K, Montoya R, et al. Defining Catastrophic Costs and Comparing Their Importance for Adverse Tuberculosis Outcome with Multi-Drug Resistance: A Prospective Cohort Study, Peru. PLoS Med. 2014;11(7).

56.

dos Santos DT, Seles Alves L, Moraes Arcoverde MA, Arroyo LH, Zamboni Berra T, Ramos ACV, et al. Social risk and its association with tuberculosis mortality in a context of high inequality in South Brazil: a geo-epidemiology analysis. J Infect Public Health. 2020 Aug 1;13(8):1148–55. https://doi.org/10.1016/j.jiph.2020.03.010.CrossRefPubMed

57.

Arcoverde MAM, Berra TZ, Alves LS, Dos Santos DT, Belchior ADS, Ramos ACV, et al. How do social-economic differences in urban areas affect tuberculosis mortality in a city in the tri-border region of Brazil. Paraguay and Argentina BMC Public Health. 2018 Jun 26;18(1):795. https://doi.org/10.1186/s12889-018-5623-2.CrossRefPubMed

58.

Reeves A, Basu S, McKee M, Stuckler D, Sandgren A, Semenza J. Social protection and tuberculosis control in 21 European countries, 1995-2012: a cross-national statistical modelling analysis. Lancet Infect Dis. 2014 Nov 1;14(11):1105–12. https://doi.org/10.1016/S1473-3099(14)70927-2.CrossRefPubMed

59.

Siroka A, Ponce NA, Lönnroth K. Association between spending on social protection and tuberculosis burden: a global analysis. Lancet Infect Dis. 2016 Apr 1;16(4):473–9. https://doi.org/10.1016/S1473-3099(15)00401-6.CrossRefPubMed

60.

Carter DJ, Glaziou P, Lönnroth K, Siroka A, Floyd K, Weil D, et al. The impact of social protection and poverty elimination on global tuberculosis incidence: a statistical modelling analysis of sustainable development goal 1. Lancet Glob Heal. 2018 May 1;6(5):e514–22. https://doi.org/10.1016/S2214-109X(18)30195-5.CrossRef

61.

Sripad A, Castedo J, Danford N, Zaha R, Freile C. Effects of Ecuador’s national monetary incentive program on adherence to treatment for drug-resistant tuberculosis. Int J Tuberc Lung Dis. 2014 Jan 1;18(1):44–8. https://doi.org/10.5588/ijtld.13.0253.CrossRefPubMed

62.

Boccia D, Hargreaves J, Lönnroth K, Jaramillo E, Weiss J, Uplekar M, Porter JDH, Evans CA Cash transfer and microfinance interventions for tuberculosis control: Review of the impact evidence and policy implications. Vol. 15, International Journal of Tuberculosis and Lung Disease. Europe PMC Funders; 2011. p. S37, Cash transfer and microfinance interventions for tuberculosis control: review of the impact evidence and policy implications, 6, S49, DOI: https://doi.org/10.5588/ijtld.10.0438.

63.

Klein K, Bernachea MP, Irribarren S, Gibbons L, Chirico C, Rubinstein F. Evaluation of a social protection policy on tuberculosis treatment outcomes: A prospective cohort study. In: Evaluation of a social protection policy on tuberculosis treatment outcomes: a prospective cohort study, vol. 16. PLoS Medicine: Public Library of Science; 2019.

64.

Ministry of Health Uganda. Uganda Population-Based HIV Impact Assessment (UPHIA) 2016-2017. 2019.

65.

Braveman PA, Cubbin C, Egerter S, Chideya S, Marchi KS, Metzler M, et al. Socioeconomic status in health research: one size does not fit all. J Am Med Assoc. 2005 Dec 14;294(22):2879–88. https://doi.org/10.1001/jama.294.22.2879.CrossRef

66.

Pollack CE, Chideya S, Cubbin C, Williams B, Dekker M, Braveman P. Should Health Studies Measure Wealth?. A Systematic Review. Vol. 33, American Journal of Preventive Medicine. Elsevier; 2007. p. 250–264, 3, DOI: https://doi.org/10.1016/j.amepre.2007.04.033.

67.

Kabudula CW, Houle B, Collinson MA, Kahn K, Gómez-Olivé FX, Tollman S, et al. Socioeconomic differences in mortality in the antiretroviral therapy era in Agincourt, rural South Africa, 2001–13: a population surveillance analysis. Lancet Glob Heal. 2017 Sep 1;5(9):e924–35. https://doi.org/10.1016/S2214-109X(17)30297-8.CrossRef

Title: Impact of socio-economic factors on Tuberculosis treatment outcomes in north-eastern Uganda: a mixed methods study
Authors: Jasper Nidoi
Winters Muttamba
Simon Walusimbi
Joseph F. Imoko
Peter Lochoro
Jerry Ictho
Levicatus Mugenyi
Rogers Sekibira
Stavia Turyahabwe
Raymond Byaruhanga
Giovanni Putoto
Simone Villa
Mario C. Raviglione
Bruce Kirenga
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Tuberculosis
Tuberculosis
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-12056-1

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Impact of socio-economic factors on Tuberculosis treatment outcomes in north-eastern Uganda: a mixed methods study

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2021

Time trends in socio-economic, urban-rural and regional disparities in prevalence of obesity among non-pregnant women in Lesotho: evidence from Lesotho demographic and health surveys (2004–2014)

Sleep problems are related to commuting accidents rather than to workplace accidents

Is Covid-19 community level testing effective in reaching at-risk populations? Evidence from spatial analysis of New Orleans patient data at walk-up sites

Challenges with social distancing during the COVID-19 pandemic among Hispanics in New York City: a qualitative study

The role of sexual compulsivity in unprotected intercourse among STI patients in Shanghai, China

NO2 exposure increases eczema outpatient visits in Guangzhou, China: an indication for hospital management