1. 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
, Kampala, UGANDA

2. 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

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

4. Household Heads by Gender
Proportion (%)
Gender
OR 5.8, 95%CI

5. 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

6. 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
Proportion (%)
L: OR 1.9, 95%CI

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<

8. 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

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

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

11. Current Source of TB Information

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

13. “…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.

14. “…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.

15. “…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

16. Knowledge of TB symptoms
Proportion (%)

17. Knowledge of TB Transmission
Proportion (%)

18. Knowledge of TB Prevention
Proportion (%)

19. Knowledge of TB Cure

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

21. What is the cost of TB treatment?

22. 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

23. 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

24. 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

25. 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

26. 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