Volume 77, Issue 6
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645


Malaria’s relationship with socioeconomic status at the macroeconomic level has been established. This is the first study to explore this relationship at the microeconomic (household) level and estimate the direction of association. Malaria prevalence was measured by parasitemia, and household socioeconomic status was measured using an asset based index. Results from an instrumental variable probit model suggest that socioeconomic status is negatively associated with malaria parasitemia. Other variables that are significantly associated with parasitemia include age of the individual, use of a mosquito net on the night before interview, the number of people living in the household, whether the household was residing at their farm home at the time of interview, household wall construction, and the region of residence. Matching estimators indicate that malaria parasitemia is associated with reduced household socioeconomic status.


Article metrics loading...

The graphs shown below represent data from March 2017
Loading full text...

Full text loading...



  1. Nayaran D, 1997. Voices of the Poor: Poverty and Social Capital in Tanzania. Washington: World Bank.
  2. Nayaran D, Patel R, Schafft K, Rademacher A, Koch-Schulte S, 2000. Voices of the Poor: Can Anyone Hear Us? New York: Oxford University Press.
  3. Case A, 2000. Health, Income and Economic Development. Princeton, NJ: World Bank, 1–39.
  4. Breman JG, 2001. The ears of the hippopotamus: manifestations, determinants, and estimates of the malaria burden. Am J Trop Med Hyg 64 : 1–11. [Google Scholar]
  5. Gallup JL, Sachs JD, 2001. The economic burden of malaria. Am J Trop Med Hyg 64 : 85–96. [Google Scholar]
  6. Sachs J, Malaney P, 2002. The economic and social burden of malaria. Nature 415 : 680–685. [Google Scholar]
  7. Malaney P, Spielman A, Sachs J, 2004. The malaria gap. Am J Trop Med Hyg 71 : 141–146. [Google Scholar]
  8. Government of Tanzania, 2001. Household Budget Survey. Dar es Salaam: Ministry of Information Services.
  9. Jowett M, Miller NJ, 2005. The financial burden of malaria in Tanzania: implications for future government policy. Int J Health Plann Manage 20 : 67–84. [Google Scholar]
  10. Robert V, Macintyre K, Keating J, Trape JF, Duchemin JB, Warren M, Beier JC, 2003. Malaria transmission in urban sub-Saharan Africa. Am J Trop Med Hyg 68 : 169–176. [Google Scholar]
  11. INDEPTH, 2002. Population and Health in Developing Countries. Ottawa: International Development Research Centre.
  12. Abdulla S, Killeen GF, 2005. MTIMBA Interim Report—Tanzania Site for INDEPTH Network. Dar es Salaam: Ifakara Health Research and Development Centre.
  13. Filmer D, Pritchett LH, 2001. Estimating wealth effects without expenditure data–or tears: an application to educational enrollments in states of India. Demography 38 : 115–132. [Google Scholar]
  14. Houweling T, Kunst A, Mackenbach J, 2003. Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter? Int J Equity Health 2 : 1–24. [Google Scholar]
  15. Casella G, Berger RL, 1990. Statistical Inference. Pacific Grove, CA: Wadsworth.
  16. Wooldridge JM, 2002. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: The MIT Press.
  17. Imbens GW, 2003. Semiparametric Estimation of Average Treatment Effects Under Exogeneity: A Review. Berkeley, CA: UC Berkley and NBER.
  18. Abadie A, Drukker D, Leber Herr J, Imbens GW, 2001. Implementing matching estimators for average treatment effects in Stata. Stata Journal 1 : 1–18. [Google Scholar]
  19. Stock JH, Yogo M, 2002. Testing for Weak Instruments in a Linear IV Regression. Cambridge, MA: National Bureau of Economic Research.
  20. Clarke SE, Bogh C, Brown RC, Pinder M, Walraven GE, Lindsay SW, 2001. Do untreated bednets protect against malaria? Trans R Soc Trop Med Hyg 95 : 457–462. [Google Scholar]
  21. Koram KA, Bennett S, Adiamah JH, Greenwood BM, 1995. Socioeconomic risk factors for malaria in a peri-urban area of The Gambia. Trans R Soc Trop Med Hyg 89 : 146–150. [Google Scholar]
  22. Tshikuka JG, Scott ME, Gray-Donald K, Kalumba ON, 1996. Multiple infection with Plasmodium and helminths in communities of low and relatively high socioeconomic status. Ann Trop Med Parasitol 90 : 277–293. [Google Scholar]
  23. Henry MC, Rogier C, Nzeyimana I, Assi SB, Dossou-Yovo J, Audibert M, Mathonnat J, Keundjian A, Akodo E, Teuscher T, Carnevale P, 2003. Inland valley rice production systems and malaria infection and disease in the savannah of Cote d’Ivoire. Trop Med Int Health 8 : 449–458. [Google Scholar]
  24. Filmer D, 2002. Fever and Its Treatment Among the More and Less Poor in Sub-Saharan Africa. Washington, DC: World Bank.
  25. Biritwum RB, Welbeck J, Barnish G, 2000. Incidence and management of malaria in two communities of different socioeconomic level, in Accra, Ghana. Ann Trop Med Parasitol 94 : 771–778. [Google Scholar]
  26. Schellenberg JA, Victora CG, Mushi A, de Savigny D, Schellenberg D, Mshinda H, Bryce J, 2003. Inequities among the very poor: health care for children in rural southern Tanzania. Lancet 361 : 561–566. [Google Scholar]
  27. Mensah OA, Kumaranayake L, 2004. Malaria incidence in rural Benin: does economics matter in endemic area? Health Policy (New York) 68 : 93–102. [Google Scholar]
  28. Uzochukwu BS, Onwujekwe OE, 2004. Socioeconomic differences and health seeking behaviour for the diagnosis and treatment of malaria: a case study of four local government areas operating the Bamako initiative programme in south-east Nigeria. Int J Equity Health 3 : 6. [Google Scholar]
  29. Njau JD, Goodman C, Kachur SP, Palmer N, Khatib RA, Abdulla S, Mills A, Bloland P, 2006. Fever treatment and household wealth: the challenge posed for rolling out combination therapy for malaria. Trop Med Int Health 11 : 299–313. [Google Scholar]
  30. Wagstaff A, 2002. Poverty and health sector inequalities. Bull World Health Organ 80 : 97–105. [Google Scholar]
  31. Baker JL, van der Gaag J, 1993. Equity in health care and health care financing: evidence from five developing countries. van Doorslaer E, Wagstaff A, Rutten F, eds. Equity in the Finance and Delivery of Health Care. Oxford: Oxford University Press, 357–394.
  32. Audibert M, Mathonnat J, Henry MC, 2003. Malaria and property accumulation in rice production systems in the savannah zone of Cote d’Ivoire. Trop Med Int Health 8 : 471–483. [Google Scholar]
  33. Girardin O, Dao D, Koudou BG, Esse C, Cisse G, Yao T, N’Goran EK, Tschannen AB, Bordmann G, Lehmann B, Nsabimana C, Keiser J, Killeen GF, Singer BH, Tanner M, Utzinger J, 2004. Opportunities and limiting factors of intensive vegetable farming in malaria endemic Cote d’Ivoire. Acta Trop 89 : 109–123. [Google Scholar]
  34. Abdulla S, Armstrong Schellenberg J, Nathan R, Mukasa O, Marchant T, Smith T, Tanner M, Lengeler C, 2001. Impact on malaria morbidity of a programme supplying insecticide treated nets in children aged under 2 years in Tanzania: community cross sectional study. BMJ 322 : 270–273. [Google Scholar]
  35. Abdulla S, Gemperli A, Mukasa O, Armstrong Schellenberg JR, Lengeler C, Vounatsou P, Smith T, 2005. Spatial effects of the social marketing of insecticide-treated nets on malaria morbidity. Trop Med Int Health 10 : 11–18. [Google Scholar]
  36. Phillips-Howard PA, Nahlen BL, Kolczak MS, Hightower AW, ter Kuile FO, Alaii JA, Gimnig JE, Arudo J, Vulule JM, Odhacha A, Kachur SP, Schoute E, Rosen DH, Sexton JD, Oloo AJ, Hawley WA, 2003. Efficacy of permethrin-treated bed nets in the prevention of mortality in young children in an area of high perennial malaria transmission in western Kenya. Am J Trop Med Hyg 68 : 23–29. [Google Scholar]
  37. Erlanger TE, Enayati AA, Hemingway J, Mshinda H, Tami A, Lengeler C, 2004. Field issues related to effectiveness of insecticide-treated nets in Tanzania. Med Vet Entomol 18 : 153–160. [Google Scholar]
  38. Guthmann JP, Hall AJ, Jaffar S, Palacios A, Lines J, Llanos-Cuentas A, 2001. Environmental risk factors for clinical malaria: a case-control study in the Grau region of Peru. Trans R Soc Trop Med Hyg 95 : 577–583. [Google Scholar]
  39. Butraporn P, Sornmani S, Hungsapruek T, 1986. Social, behavioural, housing factors and their interactive effects associated with malaria occurrence in east Thailand. Southeast Asian J Trop Med Public Health 17 : 386–392. [Google Scholar]
  40. Kahigwa E, Schellenberg D, Sanz S, Aponte JJ, Wigayi J, Mshinda H, Alonso P, Menendez C, 2002. Risk factors for presentation to hospital with severe anaemia in Tanzanian children: a case-control study. Trop Med Int Health 7 : 823–830. [Google Scholar]
  41. Gunawardena DM, Wickremasinghe AR, Muthuwatta L, Weerasingha S, Rajakaruna J, Senanayaka T, Kotta PK, Attanayake N, Carter R, Mendis KN, 1998. Malaria risk factors in an endemic region of Sri Lanka, and the impact and cost implications of risk factor-based interventions. Am J Trop Med Hyg 58 : 533–542. [Google Scholar]
  42. Gamage-Mendis AC, Carter R, Mendis C, De Zoysa AP, Herath PR, Mendis KN, 1991. Clustering of malaria infections within an endemic population: risk of malaria associated with the type of housing construction. Am J Trop Med Hyg 45 : 77–85. [Google Scholar]
  43. Konradsen F, Amerasinghe P, van der Hoek W, Amerasinghe F, Perera D, Piyaratne M, 2003. Strong association between house characteristics and malaria vectors in Sri Lanka. Am J Trop Med Hyg 68 : 177–181. [Google Scholar]
  44. Ghebreyesus TA, Haile M, Witten KH, Getachew A, Yohannes M, Lindsay SW, Byass P, 2000. Household risk factors for malaria among children in the Ethiopian highlands. Trans R Soc Trop Med Hyg 94 : 17–21. [Google Scholar]
  45. Lindsay SW, Jawara M, Paine K, Pinder M, Walraven GE, Emerson PM, 2003. Changes in house design reduce exposure to malaria mosquitoes. Trop Med Int Health 8 : 512–517. [Google Scholar]
  46. Lindsay SW, Emerson PM, Charlwood JD, 2002. Reducing malaria by mosquito-proofing houses. Trends Parasitol 18 : 510–514. [Google Scholar]
  47. Lindsay SW, Snow RW, 1988. The trouble with eaves; house entry by vectors of malaria. Trans R Soc Trop Med Hyg 82 : 645–646. [Google Scholar]
  48. Banguero H, 1984. Socioeconomic factors associated with malaria in Colombia. Soc Sci Med 19 : 1099–1104. [Google Scholar]

Data & Media loading...

  • Received : 20 Aug 2006
  • Accepted : 05 Sep 2007

Most Cited This Month

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error