Ekwaro A Obuku, M.B., Ch.B, MSc, FICRS, FICRF A comprehensive assessment of housing conditions and other social-economic determinants of Tuberculosis among dwellers in Wobulenzi Town, Lira Municipality and Makindye Division urban slum communities in Uganda Ekwaro A Obuku, M.B., Ch.B, MSc, FICRS, FICRF Lead Researcher IMF, Uganda 05.10.2011, Kampala, UGANDA

The population Characteristic Description Total Study Area Interviewed Age Mean (SD) 33.7 (12.6) Median (IQR) 30 (25 – 40) Gender Male 370 (27.1) Female 995 (72.9) Household Head No 524 (38.4) Yes 841 (61.6) Marital Status Never Married 245 (18) Cohabiting 134 (9.9) Married Mono 633 (46.5) Married Poly 125 (9.2) Widowed 109 (8) Separated 83 (6.1) Divorced 31 (2.3) 1-Men slightly older: 32 vs. 30; 2-Makindye younger:32 vs. Wobulenzi= 36, Lira=34 2-More female but males are more HHH (86% vs. 50%); female HHH driven by widowed, separated & divorced

Categories of Age in Study Sample Age Category (Years) Proportion (%)

Household Heads by Gender Proportion (%) Gender OR 5.8, 95%CI 4.2-8.1

Main Source of Livelihood None/WFP 242 (17.8) Employment Income Residence Status Citizen Local 784 (57.8) Citizen Returnee 51 (3.8) Citizen Immigrant 500 (36.9) Refugee 16 (1.2) Other 5 (0.4) Education Level Did Not Attend School 150 (11) Primary 1 – 4 149 (10.9) Primary 5 – 7 399 (29.3) Secondary 1 – 4 433 (31.7) Secondary 5 – 6 115 (8.4) Post Secondary 98 (7.2) 20 (1.5) Main Source of Livelihood None/WFP 242 (17.8) Employment Income 252 (18.5) Self Empl./Enterprise 793 (58.4) 72 (5.3) Distance from Health Unit < 0.5 km 520 (38.3) 0.5-1 km 431 (31.7) 1-5 km 352 (25.9) >5 km 55 (4) . 1-Immigration most in Makindye (50%), then Lira (37%); 2- Upper secondary education attainment more in Makindye (immigrants); 3- 70% within 1km of health unit

Residence Status by Study Area Not associated with Gender: p=0.7, p=0.4 Study Area 1-Immigration OR M-3.3, L-1.9 cf W-1; with no gender differences M-p=0.7; L-p=0.4 M: OR 3.3, 95%CI 2.5-4.5 Proportion (%) L: OR 1.9, 95%CI 1.5-2.7

Education attainment by Study Area Proportion (%) 1-Higher education attainment in Makindye; 2-More did not start school in Lira; 3-Most attained upper primary and lower secondary education Education attainment CMH, p<0.0000001

Results by objectives Assess the burden of poor housing conditions and other socioeconomic vulnerabilities for TB Determine TB Knowledge [explore Perceptions and intended health seeking Behavior] Map the available formal & informal TB services Quantify the burden of notified case of TB in 2010

Source of Information Ownership of device Proportion (%) Type of communication device

First Heard of TB First Heard of TB Proportion (%) Source of information Study Area

Current Source of TB Information

Ever Heard of TB Know cause of TB Proportion (%) Study Area Proportion (%)

“…I am a motor cyclist and through my work I get exposed to dust and air which go to the lungs. When I consulted the health workers they told me I might contract TB…” boda-boda operator in Wobulenzi Town Council.

“…in relation to housing, I think we should build houses without ventilation or when we put ventilation, we should include wire mesh to control the wind and dust that gets into the houses and causes TB…” boda-boda operator in Wobulenzi Town Council.

“…when I was still young my mother told me that you can get TB through some animals like cats, when you eat their saliva…” An 18 year old school going female youth in Makindye “…getting into physical contact with a cat can cause TB. For example when one is drinking water and fur from a cat falls into that water, it can cause TB…” male boda-boda rider in Wobulenzi

Knowledge of TB symptoms Proportion (%)

Knowledge of TB Transmission Proportion (%)

Knowledge of TB Prevention Proportion (%)

Knowledge of TB Cure

How is TB cured? Where is TB cured? Proportion (%)

What is the cost of TB treatment?

COMPLETE CASES (n=1088) IMPUTED (n=1139) p-value Table 4: Multivariate ordinal logistic regression analysis of predictors of TB knowledge score among slum dwellers in Uganda Variable COMPLETE CASES (n=1088) IMPUTED (n=1139) aOR 95% CI p-value Age 18 – 39 1 - 40 – 59 1.73 1.30 – 2.29 <0.001 1.67 1.26 – 2.20 ≥ 60 1.46 0.89 – 2.40 0.133 1.49 0.91 – 2.44 0.113 Gender Female Male 1.06 0.83 – 1.33 0.611 Education Level Secondary & above Primary 0.79 0.63 – 1.01 0.065 0.82 0.64 – 1.03 0.090 Did Not Attend School 0.56 0.38 – 0.83 0.004 0.54 0.37 – 0.79 0.001

COMPLETE CASES (n=1088) IMPUTED (n=1139) p-value Table 4: Multivariate ordinal logistic regression analysis of predictors of TB knowledge score among slum dwellers in Uganda Variable COMPLETE CASES (n=1088) IMPUTED (n=1139) aOR 95% CI p-value Source of Livelihood Self Employed 1 - Employment Income 1.22 0.91 – 1.64 0.211 0.174 None 0.67 0.49 – 0.90 0.010 0.65 0.48 – 0.88 0.005 Ever done HIV test Yes No 0.69 0.51 – 0.92 0.012 0.50 – 0.89 0.006 Distance to Health Unit < 1 km >1 km 1.16 0.90 – 1.49 0.250 1.19 0.93 – 1.51 0.171

COMPLETE CASES (n=1088) IMPUTED (n=1139) Variable COMPLETE CASES (n=1088) IMPUTED (n=1139) aOR 95% CI p-value Study Site Wobulenzi 1 - Lira 2.02 1.50 – 2.72 < 0.001 1.95 1.46 – 2.61 Makindye 0.93 0.70 – 1.23 0.611 0.92 0.70 – 1.22 0.577 Communication device* Radio (YES) 0.192 0.125 0.85 0.66 – 1.09 0.82 0.64 – 1.05 Mobile Phone (NO) 0.345 0.215 1.12 0.89 – 1.41 1.15 0. 92 – 1.44

Findings from elsewhere Singh et al 2002 Slums in New Delhi, India Only 2.3% knew TB is caused by a germ Suganthi et al 2008 Slums in Bangalore, India 2% mentioned infection with germs as its cause 36% aware cough as the crucial symptom 77% unaware of free Dx & Rx for TB TB curable according to 19% 7% knew duration of Rx varied 6 to 8 mo

Conclusions TB Partnership Housing Important problem Poor KAB Lack of services Barriers to care Housing Poor Promotes TB Partnership Residents Participatory planning Namuwongo case study NTLP, CSOs, Urban planning authorities