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Imesidayo Omua Eboreime-Oikeh (PhD, Kenyatta University) Amref Health Africa International Conference (AHAIC) Safari Park Hotel Nairobi, Kenya November.

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Presentation on theme: "Imesidayo Omua Eboreime-Oikeh (PhD, Kenyatta University) Amref Health Africa International Conference (AHAIC) Safari Park Hotel Nairobi, Kenya November."— Presentation transcript:

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

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 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 CharacteristicsMalesFemalesTotal Age (years) p=0.002 n ( %) < (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< < (59)488 (91.9) 599 (83.3) ≥ (41)43 (8.1) 120 (16.7) Employed p< No 19 (10.1)235 (44.3) 254 (34.1) Yes 169 (89.9)296 (54.7) 465 (65.9) Total 188 (26.1)531 (73.9)719 (100)

7 Prevalence of *Self-Reported Hypertension per Village in Korogocho Informal Settlement Gitathuru 5.6% Grogan A 6% Grogan B 7.9% Highridge 3% Kisumu Ndogo 15.7% Korogocho A 9.8% Korogocho B 6.7% Ngomongo 6.3% Nyayo 10% Total in Korogocho Informal Settlement 7.4% Village Prevalence of Hypertension ¶ *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 MaleFemaleTotal Hypertensionn (%) No178 (94.7)488 (91.9) 666 (92.6) Yes 10 (5.3) 43 (8.1)53 (7.4) HIV/AIDS n (%) No185 (98.4)502 (94.5)687 (95.6) Yes3 (1.6)29 (5.5)32 (4.4)

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 years46 (6.6)648 (93.4) OR, % CI, p=.0003 ≥ 45 years7 (28)18 (72) Male10 (5.3)178 (94.7) OR, % CI, p=.21 Female43 (8.1)488 (91.9) Single status2 (2.6)76 (97.4) OR, % CI, p=.04 Widowed7 (13)47 (87) *Socioeconomic status (Education, Employment, Income) OR, % CI, p=.013 Education among men Poor self-rated health status 26 (13.8)163 (86.2) OR, % CI, p=.0002 Good self-rated health status 27 (5.1)503 (94.9) Landlord11 (16.9)54 (83.1) OR, % CI, p=.004 Tenant38 (6.5)546 (93.5) *Lifestyle (Tobacco, Alcohol, Physical Activity) Physical Activity among men OR, % CI, p=.03

13 Logistic Regression Analysis for Predictors of Hypertension-related Health Inequalities Among Men BS.EWalddfSigExp (B) 95% C.I. for EXP (B) Lower Upper age widowhood *SRH house ownership education physical activity Constant 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 Strengths 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

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