Skip to main content
Top
Published in: Malaria Journal 1/2018

Open Access 01-12-2018 | Research

Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour

Authors: Vincent Were, Ann M. Buff, Meghna Desai, Simon Kariuki, Aaron Samuels, Feiko O. ter Kuile, Penelope A. Phillips-Howard, S. Patrick Kachur, Louis Niessen

Published in: Malaria Journal | Issue 1/2018

Login to get access

Abstract

Background

Health inequality is a recognized barrier to achieving health-related development goals. Health-equality data are essential for evidence-based planning and assessing the effectiveness of initiatives to promote equity. Such data have been captured but have not always been analysed or used to manage programming. Health data were examined for microeconomic differences in malaria indices and associated malaria control initiatives in western Kenya.

Methods

Data was analysed from a malaria cross-sectional survey conducted in July 2012 among 2719 people in 1063 households in Siaya County, Kenya. Demographic factors, history of fever, malaria parasitaemia, malaria medication usage, insecticide-treated net (ITN) use and expenditure on malaria medications were collected. A composite socioeconomic status score was created using multiple correspondence analyses (MCA) of household assets; households were classified into wealth quintiles and dichotomized into poorest (lowest 3 quintiles; 60%) or less-poor (highest 2 quintiles; 40%). Prevalence rates were calculated using generalized linear modelling.

Results

Overall prevalence of malaria infection was 34.1%, with significantly higher prevalence in the poorest compared to less-poor households (37.5% versus 29.2%, adjusted prevalence ratio [aPR] 1.23; 95% CI = 1.08–1.41, p = 0.002). Care seeking (aPR = 0.95; 95% CI 0.87–1.04, p = 0.229), medication use (aPR = 0.94; 95% CI 0.87–1.00, p = 0.087) and ITN use (aPR = 0.96; 95% CI = 0.87–1.05, p = 0.397) were similar between households. Among all persons surveyed, 36.4% reported taking malaria medicines in the prior 2 weeks; 92% took artemether-lumefantrine, the recommended first-line malaria medication. In the poorest households, 4.9% used non-recommended medicines compared to 3.5% in less-poor (p = 0.332). Mean and standard deviation [SD] for expenditure on all malaria medications per person was US$0.38 [US$0.50]; the mean was US$0.35 [US$0.52] amongst the poorest households and US$0.40 [US$0.55] in less-poor households (p = 0.076). Expenditure on non-recommended malaria medicine was significantly higher in the poorest (mean US$1.36 [US$0.91]) compared to less-poor households (mean US$0.98 [US$0.80]; p = 0.039).

Conclusions

Inequalities in malaria infection and expenditures on potentially ineffective malaria medication between the poorest and less-poor households were evident in rural western Kenya. Findings highlight the benefits of using MCA to assess and monitor the health-equity impact of malaria prevention and control efforts at the microeconomic level.
Literature
1.
go back to reference Guillot M, Gwatkin DR. The burden of disease among the global poor: current situation, future trends, and implications for strategy. World Bank: Global Forum for Health Research; 1999. Guillot M, Gwatkin DR. The burden of disease among the global poor: current situation, future trends, and implications for strategy. World Bank: Global Forum for Health Research; 1999.
2.
go back to reference Lopez AD, Mathers CD. Measuring the global burden of disease and epidemiological transitions: 2002–2030. Ann Trop Med Parasitol. 2006;100:481–99.CrossRefPubMed Lopez AD, Mathers CD. Measuring the global burden of disease and epidemiological transitions: 2002–2030. Ann Trop Med Parasitol. 2006;100:481–99.CrossRefPubMed
3.
go back to reference WHO. World malaria report 2016. Geneva: World Health Organization; 2016. WHO. World malaria report 2016. Geneva: World Health Organization; 2016.
4.
go back to reference Mohajan HK. Improvement of health sector in Kenya. Am J Public Health Res. 2014;2:159–69.CrossRef Mohajan HK. Improvement of health sector in Kenya. Am J Public Health Res. 2014;2:159–69.CrossRef
5.
go back to reference Programme National Malaria Control. Kenya malaria indicator survey 2015. Nairobi, Kenya and Rockville, Maryland, USA: NMCP, KNBS, and ICF Int; 2016. Programme National Malaria Control. Kenya malaria indicator survey 2015. Nairobi, Kenya and Rockville, Maryland, USA: NMCP, KNBS, and ICF Int; 2016.
6.
go back to reference de Castro MC, Fisher MG. Is malaria illness among young children a cause or a consequence of low socioeconomic status? evidence from the united Republic of Tanzania. Malar J. 2012;11:161.CrossRefPubMedPubMedCentral de Castro MC, Fisher MG. Is malaria illness among young children a cause or a consequence of low socioeconomic status? evidence from the united Republic of Tanzania. Malar J. 2012;11:161.CrossRefPubMedPubMedCentral
7.
go back to reference Worrall E, Basu S, Hanson K. Is malaria a disease of poverty? A review of the literature. Trop Med Int Health. 2005;10:1047–59.CrossRefPubMed Worrall E, Basu S, Hanson K. Is malaria a disease of poverty? A review of the literature. Trop Med Int Health. 2005;10:1047–59.CrossRefPubMed
9.
go back to reference Chuma J, Okungu V, Molyneux C. The economic costs of malaria in four Kenyan districts: do household costs differ by disease endemicity? Malar J. 2010;9:149.CrossRefPubMedPubMedCentral Chuma J, Okungu V, Molyneux C. The economic costs of malaria in four Kenyan districts: do household costs differ by disease endemicity? Malar J. 2010;9:149.CrossRefPubMedPubMedCentral
10.
go back to reference Somi MF, Butler JR, Vahid F, Njau J, Kachur SP, Abdulla S. Is there evidence for dual causation between malaria and socioeconomic status? Findings from rural Tanzania. Am J Trop Med Hyg. 2007;77:1020–7.PubMed Somi MF, Butler JR, Vahid F, Njau J, Kachur SP, Abdulla S. Is there evidence for dual causation between malaria and socioeconomic status? Findings from rural Tanzania. Am J Trop Med Hyg. 2007;77:1020–7.PubMed
11.
go back to reference Chima RI, Goodman CA, Mills A. The economic impact of malaria in Africa: a critical review of the evidence. Health Policy. 2003;63:17–36.CrossRefPubMed Chima RI, Goodman CA, Mills A. The economic impact of malaria in Africa: a critical review of the evidence. Health Policy. 2003;63:17–36.CrossRefPubMed
12.
go back to reference Goodman C, Kara H, Anne M, Virginia W, Worrall E. The economics of malaria and its control. Scientific Working Group on Malaria. WHO/TDR: Geneva; 2003. Goodman C, Kara H, Anne M, Virginia W, Worrall E. The economics of malaria and its control. Scientific Working Group on Malaria. WHO/TDR: Geneva; 2003.
13.
go back to reference Houweling TA, Kunst AE, Mackenbach JP. Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter? Int J Equity Health. 2003;2:8.CrossRefPubMedPubMedCentral Houweling TA, Kunst AE, Mackenbach JP. Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter? Int J Equity Health. 2003;2:8.CrossRefPubMedPubMedCentral
14.
go back to reference Kolenikov S, Angeles G. The use of discrete data in PCA: theory, simulations, and applications to socioeconomic indices. Chapel Hill: Carolina Population Center, University of North Carolina; 2004. p. 1–59. Kolenikov S, Angeles G. The use of discrete data in PCA: theory, simulations, and applications to socioeconomic indices. Chapel Hill: Carolina Population Center, University of North Carolina; 2004. p. 1–59.
15.
go back to reference Kolenikov S, Angeles G. The use of discrete data in principal component analysis for socio-economic status evaluation. Carolina, NC: University of North Carolina at Chapel Hill; 2005. Kolenikov S, Angeles G. The use of discrete data in principal component analysis for socio-economic status evaluation. Carolina, NC: University of North Carolina at Chapel Hill; 2005.
16.
go back to reference McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ. 2005;18:229–60.CrossRef McKenzie DJ. Measuring inequality with asset indicators. J Popul Econ. 2005;18:229–60.CrossRef
17.
go back to reference WHO. Handbook on health inequality monitoring with a special focus on low-and middle-income countries. Geneva: World Health Organization; 2013. WHO. Handbook on health inequality monitoring with a special focus on low-and middle-income countries. Geneva: World Health Organization; 2013.
18.
go back to reference Sherraden M, Gilbert N. Assets and the poor: new American welfare policy. Abingdon: Routledge; 2016. Sherraden M, Gilbert N. Assets and the poor: new American welfare policy. Abingdon: Routledge; 2016.
19.
go back to reference Somi MF, Butler JR, Vahid F, Njau JD, Kachur SP, Abdulla S. Use of proxy measures in estimating socioeconomic inequalities in malaria prevalence. Trop Med Int Health. 2008;13:354–64.CrossRefPubMed Somi MF, Butler JR, Vahid F, Njau JD, Kachur SP, Abdulla S. Use of proxy measures in estimating socioeconomic inequalities in malaria prevalence. Trop Med Int Health. 2008;13:354–64.CrossRefPubMed
20.
go back to reference Amek N, Vounatsou P, Obonyo B, Hamel M, Odhiambo F, Slutsker L, et al. Using health and demographic surveillance system (HDSS) data to analyze geographical distribution of socio-economic status; an experience from KEMRI/CDC HDSS. Acta Trop. 2015;144:24–30.CrossRefPubMed Amek N, Vounatsou P, Obonyo B, Hamel M, Odhiambo F, Slutsker L, et al. Using health and demographic surveillance system (HDSS) data to analyze geographical distribution of socio-economic status; an experience from KEMRI/CDC HDSS. Acta Trop. 2015;144:24–30.CrossRefPubMed
21.
go back to reference Abdi H, Valentin D. Multiple correspondence analysis. Encyclopedia of measurement and statistics. 2007;651–7. Abdi H, Valentin D. Multiple correspondence analysis. Encyclopedia of measurement and statistics. 2007;651–7.
22.
go back to reference Su-Myat KK, de Tibeiro JJ, Kumar P. An integrated approach to regression analysis in multiple correspondence analysis and copula based models. J Stat Applic Probab. 2012;1:1.CrossRef Su-Myat KK, de Tibeiro JJ, Kumar P. An integrated approach to regression analysis in multiple correspondence analysis and copula based models. J Stat Applic Probab. 2012;1:1.CrossRef
23.
go back to reference Adazu K, Lindblade KA, Rosen DH, Odhiambo F, Ofware P, Kwach J, et al. Health and demographic surveillance in rural western Kenya: a platform for evaluating interventions to reduce morbidity and mortality from infectious diseases. Am J Trop Med Hyg. 2005;73:1151–8.PubMed Adazu K, Lindblade KA, Rosen DH, Odhiambo F, Ofware P, Kwach J, et al. Health and demographic surveillance in rural western Kenya: a platform for evaluating interventions to reduce morbidity and mortality from infectious diseases. Am J Trop Med Hyg. 2005;73:1151–8.PubMed
24.
go back to reference Hamel MJ, Adazu K, Obor D, Sewe M, Vulule J, Williamson JM, et al. A reversal in reductions of child mortality in western Kenya, 2003–2009. Am J Trop Med Hyg. 2011;85:597–605.CrossRefPubMedPubMedCentral Hamel MJ, Adazu K, Obor D, Sewe M, Vulule J, Williamson JM, et al. A reversal in reductions of child mortality in western Kenya, 2003–2009. Am J Trop Med Hyg. 2011;85:597–605.CrossRefPubMedPubMedCentral
25.
go back to reference Odhiambo FO, Laserson KF, Sewe M, Hamel MJ, Feikin DR, Adazu K, et al. Profile: the KEMRI/CDC health and demographic surveillance system—Western Kenya. Int J Epidemiol. 2012;41:977–87.CrossRefPubMed Odhiambo FO, Laserson KF, Sewe M, Hamel MJ, Feikin DR, Adazu K, et al. Profile: the KEMRI/CDC health and demographic surveillance system—Western Kenya. Int J Epidemiol. 2012;41:977–87.CrossRefPubMed
26.
go back to reference Kenya National Bureau of Statistics (KNBS) and ICF Macro. Kenya demographic and health survey 2008–09. Maryland, USA: Calverton; 2010. Kenya National Bureau of Statistics (KNBS) and ICF Macro. Kenya demographic and health survey 2008–09. Maryland, USA: Calverton; 2010.
27.
go back to reference Kenya National Bureau of Statistics (KNBS) and ICF Macro. Kenya demographic and health survey 2014. Maryland, USA: Calverton; 2015. Kenya National Bureau of Statistics (KNBS) and ICF Macro. Kenya demographic and health survey 2014. Maryland, USA: Calverton; 2015.
28.
go back to reference Division of Malaria Control. National guidelines for the diagnosis, treatment and prevention of malaria in Kenya. Nairobi Kenya: Kenya Ministry of Public Health and Sanitation; 2012. Division of Malaria Control. National guidelines for the diagnosis, treatment and prevention of malaria in Kenya. Nairobi Kenya: Kenya Ministry of Public Health and Sanitation; 2012.
29.
go back to reference Kioko U, Riley C, Dellicour S, Were V, Ouma P, Gutman J, et al. A cross-sectional study of the availability and price of anti-malarial medicines and malaria rapid diagnostic tests in private sector retail drug outlets in rural Western Kenya, 2013. Malar J. 2016;15:359.CrossRefPubMedPubMedCentral Kioko U, Riley C, Dellicour S, Were V, Ouma P, Gutman J, et al. A cross-sectional study of the availability and price of anti-malarial medicines and malaria rapid diagnostic tests in private sector retail drug outlets in rural Western Kenya, 2013. Malar J. 2016;15:359.CrossRefPubMedPubMedCentral
30.
go back to reference Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21:459–68.CrossRefPubMed Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21:459–68.CrossRefPubMed
31.
go back to reference Machini B, Nyandigisi A, Kigen S, Memusi D, Kimbui R, Mulinga J. Monitoring outpatient malaria case management under the 2010 diagnostic and treatment policy in Kenya: progress 2010–2014. Nairobi: Ministry of Health; 2014. Machini B, Nyandigisi A, Kigen S, Memusi D, Kimbui R, Mulinga J. Monitoring outpatient malaria case management under the 2010 diagnostic and treatment policy in Kenya: progress 2010–2014. Nairobi: Ministry of Health; 2014.
32.
go back to reference Cohen J, Dupas P, Schaner S. Price subsidies, diagnostic tests, and targeting of malaria treatment: evidence from a randomized controlled trial. Am Econ Rev. 2015;105:609–45.CrossRef Cohen J, Dupas P, Schaner S. Price subsidies, diagnostic tests, and targeting of malaria treatment: evidence from a randomized controlled trial. Am Econ Rev. 2015;105:609–45.CrossRef
33.
go back to reference Riley C, Dellicour S, Ouma P, Kioko U, ter Kuile FO, Omar A, et al. Knowledge and adherence to the national guidelines for malaria case management in pregnancy among healthcare providers and drug outlet dispensers in rural, western Kenya. PLoS ONE. 2016;11:e0145616.CrossRefPubMedPubMedCentral Riley C, Dellicour S, Ouma P, Kioko U, ter Kuile FO, Omar A, et al. Knowledge and adherence to the national guidelines for malaria case management in pregnancy among healthcare providers and drug outlet dispensers in rural, western Kenya. PLoS ONE. 2016;11:e0145616.CrossRefPubMedPubMedCentral
34.
go back to reference Ministry of Public Health and Sanitation MOPHS): National Malaria Strategy 2009-2017. (Control DoM ed. Nairobi, Kenya: Division of Malaria Control; 2009. Ministry of Public Health and Sanitation MOPHS): National Malaria Strategy 2009-2017. (Control DoM ed. Nairobi, Kenya: Division of Malaria Control; 2009.
35.
go back to reference Kenya Ministry of Health (MOH): Kenya Health Policy 2014-2030—towards attaining the highest standard of health. (health Mo ed. Nairobi, Kenya: Kenya Ministry of Health; 2014. Kenya Ministry of Health (MOH): Kenya Health Policy 2014-2030—towards attaining the highest standard of health. (health Mo ed. Nairobi, Kenya: Kenya Ministry of Health; 2014.
36.
go back to reference Nam UV. Transforming our world: the 2030 agenda for sustainable development. 2015. Nam UV. Transforming our world: the 2030 agenda for sustainable development. 2015.
Metadata
Title
Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour
Authors
Vincent Were
Ann M. Buff
Meghna Desai
Simon Kariuki
Aaron Samuels
Feiko O. ter Kuile
Penelope A. Phillips-Howard
S. Patrick Kachur
Louis Niessen
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Malaria Journal / Issue 1/2018
Electronic ISSN: 1475-2875
DOI
https://doi.org/10.1186/s12936-018-2319-0

Other articles of this Issue 1/2018

Malaria Journal 1/2018 Go to the issue