1. Emerging Threat Of Hypertension Among The Urban Poor in a Nairobi Informal Settlement
Imesidayo Omua Eboreime-Oikeh
(PhD, Kenyatta University)
Amref Health Africa International Conference (AHAIC)
Safari Park Hotel Nairobi, Kenya
November 24-26, 2014

2. Background
Hypertension: BP ≥ 140/90 is one of the leading risk factors for CVD, which constitutes 48% of NCDs (Roger, Go, Lloyd-Jones, et al. 2012)
Worldwide 972 million people living with hypertension (Kearney, Whelton, Reynolds, Muntner, Whelton, & He, 2005)
LMICs account for 85% of 14 million deaths annually from preventable NCDs particularly among working age adults (UN 2011)
Demographic & epidemiologic transitions are driving the rise in prevalence of NCDs in urban areas in LMICs where majority of population reside in informal settlements (UN 2008)
But, there is limited information on the socio-demographic factors that are associated with the unequal distribution of hypertension among the working age group in urban informal settlements (WHO CSDH, 2008)
Health inequalities refer to systemic differences in the distribution of health or disease between and within population groups

3. Objectives
Determine the prevalence of self-reported hypertension in a representative sample of adults aged years in Korogocho, a Nairobi Informal Settlement
Identify the determinants of hypertension-related health inequalities among adult men and women in Korogocho

4. Methods Study Design Sampling Technique & Study Population
Cross-sectional, observational, population based study undertaken in Korogocho Informal Settlement, Nairobi, Kenya from August to October 2012
Pre-tested structured questionnaires in English and Kiswahili
No physical measurements or lab investigations were done
No external funding
Sampling Technique & Study Population
Multi-stage, mixed cluster probability sample from each of the nine villages in Korogocho
Consenting adult men and women aged between 25 and 59 years who have lived continuously in the villages for at least one year
Oversight: KU-ERC, NCST&I
Statistical Analysis
SPSS v 20; 95% CI, Two-tailed p-value<0.05 for significance

5. Korogocho Informal Settlement
Source: Pamoja Trust, 2009

6. Results Characteristics of Study Population
Males
Females
Total
Age (years) p=0.002
n ( %)
n (%)
<45
176 (93.6)
518 (97.6)
694 (96.5)
≥45
12 (6.4)
13 (2.4)
25 (3.5)
Marital Status p=0.026
Not widowed
181 (96.3)
484 (91.2)
665 (92.5)
Widowed
7 (3.7)
47 (8.8)
54 (7.5)
Education p=0.009
None
14 (7.5)
80 (15.1)
94 (13.1)
Some
174 (92.5)
451 (84.9)
625 (86.9)
Income (KES/mth) p<0.0001
<5 000
111 (59)
488 (91.9)
599 (83.3)
≥5 000
77 (41)
43 (8.1)
120 (16.7)
Employed p<0.0001 No
19 (10.1)
235 (44.3)
254 (34.1)
Yes
169 (89.9)
296 (54.7)
465 (65.9)
188 (26.1)
531 (73.9)
719 (100)
Average age was 34.2 (SD 8.7) years but males (35.9, SD 8.3) years compared to females (33.6, SD 8.7) years p= KIPPRA OF 2013 Economic Report 10% of Kenya Population never attended school. Some education but not literacy rate. Unemployment in Kenya 8.6%. Remember underemployment

7. Prevalence of *Self-Reported Hypertension per Village in Korogocho Informal Settlement
Prevalence of Hypertension
Gitathuru %
Grogan A %
Grogan B %
Highridge %
Kisumu Ndogo %
Korogocho A %
Korogocho B %
Ngomongo %
Nyayo %
Total in Korogocho Informal Settlement %
*Self-reported Hypertension found to be sensitive with good overall accuracy for chronic disease survey (Thai Cohort Study Team, 2013) ¶ OR 2.34, 95% CI , p<0.02

8. Kisumu Ndogo was the only village with a health disadvantage in prevalence of hypertension compared to the average in Korogocho Informal Settlement
Prevalence in Africa varies from 9.4% in Ethiopia (Muluneh, Haileamlak, Tessema, Alemseged, Woldemichael, Asefa, et al., 2012) to 49% in Mozambique (Damasceno, Azevedo, Silva- Matos, Prista, Diogo, & Lunet, 2009)
Heterogeneity of sampled populations partly accounts for differences in reported prevalence
Relatively low prevalence of hypertension in this study could be attributed to self-reported crude prevalence of hypertension in a population with low awareness and underserved with few & inadequate health systems (van de Vijver et al, 2013)

9. Prevalence of Self-Reported Hypertension and HIV/AIDS
Male
Female
Total
Hypertension
n (%) No
178 (94.7)
488 (91.9)
666 (92.6)
Yes
10 (5.3)
43 (8.1)
53 (7.4)
HIV/AIDS
185 (98.4)
502 (94.5)
687 (95.6)
3 (1.6)
29 (5.5)
32 (4.4)
2 (2.8%) PEOPLE HAD BOTH HYPERTENSION AND HIV/AIDS

10. Prevalence of Hypertension compared to HIV/AIDS
Difference in Overall Prevalence, p=0.02; 2 (0.28%) reported both HTN & HIV/AIDS

11. Reporting bias possible
Both hypertension and HIV infection are largely asymptomatic early
Diagnosis requires contact with health care practitioners/facilities, which are inaccessible for many in informal settlements
Stigma associated with HIV/AIDS and to a lesser extent with hypertension (Smith, 2009)
Comparison between hypertension and HIV/AIDS:
Both are lifestyle diseases (Remais, Zeng, Li, Tian, & Engelgau, 2012)
Like HIV/AIDS early in the epidemic, the public health response to burden of Hypertension in developing countries particularly disadvantaged areas has been slow and inadequate (Lloyd-Sherlock, Ebrahim, & Grosskurth, 2014)

12. Determinants of Hypertension-related Health Inequalities
Characteristics
Hypertension
Yes No
n (%) n (%)
< 45 years
46 (6.6)
648 (93.4)
OR, 5.48
95% CI,
p=.0003
≥ 45 years
7 (28)
18 (72)
Male
10 (5.3)
178 (94.7)
OR, 1.57
95% CI,
p=.21
Female
43 (8.1)
488 (91.9)
Single status
2 (2.6)
76 (97.4)
OR, 5.6
95% CI,
p=.04
Widowed
7 (13)
47 (87)
*Socioeconomic status
(Education, Employment, Income)
OR, 1.2
95% CI,
p=.013
Education among men
Poor self-rated health status
26 (13.8)
163 (86.2)
OR, 2.97
95% CI,
p=.0002
Good self-rated health status
27 (5.1)
503 (94.9)
Landlord
11 (16.9)
54 (83.1)
OR, 2.93
95% CI,
p=.004
Tenant
38 (6.5)
546 (93.5)
*Lifestyle
(Tobacco, Alcohol, Physical Activity)
Physical Activity among men OR, 0.186
95% CI,
p=.03

13. Logistic Regression Analysis for Predictors of Hypertension-related Health Inequalities Among MenB
S.E
Wald df
Sig
Exp (B)
95% C.I. for EXP (B)
Lower Upper
age
.039
.012
10.937 1
.001
1.040
1.016
1.064
widowhood
.523
.299
2.976
.084
2.048
.907
4.622
*SRH
.709
.267
7.033
.008
2.031
1.203
3.430
house ownership
.875
.444
3.876
.049
2.399
1.004
5.733
education
1.146
.554
4.282
3.146
1.062
9.314
physical activity
1.003
.441
5.177
.023
2.726
1.149
6.465
Constant
-1.676
3.336
.253
.615
.187
Variables entered: age, widowhood, SRH, house ownership, education, physical activity
*SRH=Self-rated health

14. Prevalence of hypertension in in two informal settlements in Nairobi was 12.3% (12.7% in women; 12.0% in men) but in study by Ongeti et al, 2013, prevalence of hypertension was more in males in Kibera (17.8% vs 11.1%; p=0.001) and increasing age
Women live more with chronic diseases & report poorer self-rated health than men (Malmusi from Barcelona, 2011)
Awareness of hypertension as low as 19.5% among residents of some Nairobi informal settlements (van de Vijver, Oti, Agyemang, Gomez, & Kyobutungi, 2013)
Gender differences in socioeconomic determinants of hypertension- related health inequalities compare with SA findings & attributed to unmeasured confounding factors (Cois & Ehrlich, 2014)
Physical inactivity linked to hypertension (Joshi, et al., 2014; Salehmohamed, 2010) but not smoking or alcohol in this study

15. Strengths & Limitations
Primary data from disadvantaged community
Disaggregated data
Gender
Place
Limitations
Unintended oversampling of women possibly because daytime collection of data but made up for by stratified analysis to mitigate selection bias
Self-report of Hypertension and HIV/AIDS

16. Conclusions & Recommendations
Significant burden of the NCD risk factor - Hypertension among the urban poor with higher prevalence than HIV/AIDS, a communicable disease
Though Hypertension more prevalent among women, determinants of Hypertension-related Health Inequalities more among men
Socioeconomic health inequalities only with education in men
Physical activity was an important determinant of inequality in the population with problems of congestion and lack of recreational facilities reminiscent of informal settlements
Emerging threat of Hypertension in SSA and among urban poor should be recognized, integrated & tackled side by side with communicable diseases
Targeting of determinants of health inequalities important for resource allocation & evaluation of disease-mitigation strategies to achieve UHC and development goals

17. Further Research Identify:
factors that promote burden of hypertension among the urban poor
reasons for gender-based differences in determinants of health inequalities
linkages between hypertension & barriers to achievement of MDGs in SSA
implications of the emerging threat of NCDs in SSA for sustainable growth in post-2015 development framework

18. Thank you