1921
Volume 94, Issue 3
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Abstract

Socioeconomic position (SEP) is an important risk factor for malaria, but there is no consensus on how to measure SEP in malaria studies. We evaluated the relative strength of four indicators of SEP in predicting malaria risk in Nagongera, Uganda. A total of 318 children resident in 100 households were followed for 36 months to measure parasite prevalence routinely every 3 months and malaria incidence by passive case detection. Household SEP was determined using: 1) two wealth indices, 2) income, 3) occupation, and 4) education. Wealth Index I (reference) included only asset ownership variables. Wealth Index II additionally included food security and house construction variables, which may directly affect malaria. In multivariate analysis, only Wealth Index II and income were associated with the human biting rate, only Wealth Indices I and II were associated with parasite prevalence, and only caregiver's education was associated with malaria incidence. This is the first evaluation of metrics beyond wealth and consumption indices for measuring the association between SEP and malaria. The wealth index still predicted malaria risk after excluding variables directly associated with malaria, but the strength of association was lower. In this setting, wealth indices, income, and education were stronger predictors of socioeconomic differences in malaria risk than occupation.

Loading

Article metrics loading...

/content/journals/10.4269/ajtmh.15-0554
2016-03-02
2017-11-20
Loading full text...

Full text loading...

/deliver/fulltext/14761645/94/3/650.html?itemId=/content/journals/10.4269/ajtmh.15-0554&mimeType=html&fmt=ahah

References

  1. Tusting LS, Willey B, Lucas H, Thompson J, Kafy HT, Smith R, Lindsay S, , 2013. Socioeconomic development as an intervention against malaria: a systematic review and meta-analysis. Lancet 382: 963972.[Crossref]
  2. Lynch J, Kaplan G, Berkman L, Kawachi I, , 2000. Socioeconomic position. , eds. Social Epidemiology. New York, NY: Oxford University Press, 1335.
  3. Boccia D, Hargreaves J, De Stavola B, Fielding K, Schaap A, , 2011. The association between household socioeconomic position and prevalent tuberculosis in Zambia: a case-control study. PLoS One 6: e20824.[Crossref]
  4. Shavers V, , 2007. Measurement of socioeconomic status in health disparities research. J Natl Med Assoc 99: 10131023.
  5. Braveman P, Cubbin C, Egerter S, Chideya S, Marchi K, , 2005. Socioeconomic status in health research: one size does not fit all. JAMA 294: 28792888.[Crossref]
  6. Howe L, Galobardes B, Matijasevich A, Gordon D, Johnston D, Onwujekwe O, Patel R, Webb EA, Lawlor DA, Hargreaves JR, , 2012. Measuring socio-economic position for epidemiological studies in low- and middle-income countries: a methods of measurement in epidemiology paper. Int J Epidemiol 41: 871886.[Crossref]
  7. Deaton A, Zaidi S, , 1999. Guidelines for Constructing Consumption Aggregates for Welfare Analysis. Princeton, NJ: World Bank.
  8. Makinen M, Waters H, Rauch M, , 2000. Inequalities in health care use and expenditures: empirical data from eight developing countries and countries in transition. Bull World Health Organ 78: 5565.
  9. Fisher M, Reimer JJ, Carr ER, , 2010. Who Should Be Interviewed in Surveys of Household Income? Washington, DC: International Food Policy Research Institute.
  10. Montgomery M, Gragnolati M, Burke K, Paredes E, , 2000. Measuring living standards with proxy variables. Demography 37: 155174.[Crossref]
  11. Filmer D, Pritchett LH, , 2001. Estimating wealth effects without expenditure data-or tears: an application to educational enrolments in states of India. Demography 38: 115132.
  12. Houweling TA, Kunst AE, Mackenbach JP, , 2003. Measuring health inequality among children in developing countries: does the choice of the indicator of economic status matter? Int J Equity Health 2: 8.[Crossref]
  13. Howe LD, Hargreaves JR, Gabrysch S, Huttly SRA, , 2009. Is the wealth index a proxy for consumption expenditure? A systematic review. J Epi Comm Health 63: 871877.[Crossref]
  14. Boccia D, Hargreaves J, Howe L, De Stavola B, Fielding K, Ayles H, Godfrey-Faussett P, , 2013. The measurement of household socio-economic position in tuberculosis prevalence surveys: a sensitivity analysis. Int J Tuberc Lung Dis 17: 3945.[Crossref]
  15. Rutstein SO, , 2015. Steps to Constructing the New DHS Wealth Index. Rockville, MD: ICF International.
  16. Vyas S, Kumuranayake L, , 2006. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan 6: 459468.[Crossref]
  17. Tusting LS, Ippolito M, Kleinschmidt I, Willey B, Gosling R, Dorsey G, Lindsay S, , 2015. The evidence for improving housing to reduce malaria: a systematic review and meta-analysis. Malar J 14: 209.[Crossref]
  18. Ganzeboom HBG, Treiman DJ, Stephenson E, , 2009. The International Stratification and Mobility File, 2009. Available at: http://www.harryganzeboom.nl/ISMF/index.htm.
  19. Galobardes S, Lawlor MS, Lynch DA, Davey JW, Smith G, , 2006. Indicators of socioeconomic position (Part 1). J Epidemiol Community Health 60: 712.[Crossref]
  20. Galobardes S, Lawlor MS, Lynch DA, Davey JW, Smith G, , 2006. Indicators of socioeconomic position (Part 2). J Epidemiol Community Health 60: 95101.[Crossref]
  21. Sahn DE, Stifel D, , 2003. Exploring alternative measures of welfare in the absence of expenditure data. Rev Income Wealth 49: 463489.[Crossref]
  22. Morris SS, Carletto C, Hoddinot J, Christiaensen LJM, , 2000. Validity of rapid estimates of household wealth and income for health surveys in rural Africa. J Epidemiol Community Health 54: 381387.[Crossref]
  23. Scoones I, , 1995. Investigating difference: applications of wealth ranking and household survey approaches among farming households in southern Zimbabwe. Dev Change 26: 6788.[Crossref]
  24. Howe LD, Hargreaves JR, Huttly SR, , 2008. Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries. Emerg Themes Epidemiol 5: 3.[Crossref]
  25. Lindelow M, , 2006. Sometimes more equal than others: how health inequalities depend on the choice of welfare indicator. Health Econ 15: 263279.[Crossref]
  26. Wamani H, Tylleskär T, Astrøm A, Tumwine J, Peterson S, , 2004. Mothers' education but not fathers' education, household assets or land ownership is the best predictor of child health inequalities in rural Uganda. Int J Equity Health 13: 9.[Crossref]
  27. Hargreaves JR, Morison LA, Gear GSS, , 2007. Assessing household wealth in health studies in developing countries: a comparison of participatory wealth ranking in rural South Africa. Emerg Themes Epidemiol 4: 4.[Crossref]
  28. Somi M, Butler J, Vahid F, Njau J, Kachur S, Abdulla S, , 2008. Use of proxy measures in estimating socioeconomic inequalities in malaria prevalence. Trop Med Int Health 13: 354364.[Crossref]
  29. Maxwell K, Smith DL, Hutchinson R, Kigozi R, Lavoy G, Kamya MR, Staedke S, Donnelly MJ, Drakeley C, Dorsey G, Lindsay SW, , 2014. Estimating the annual entomological inoculation rate for Plasmodium falciparum transmitted by Anopheles gambiae s.l. using three sampling methods in three sites in Uganda. Malar J 13: 111.[Crossref]
  30. Kamya MR, Arinaitwe E, Wanzira H, Katureebe A, Barusya C, Kigozi SP, Kilama M, Tatem AJ, Rosenthal PJ, Drakeley C, Lindsay SW, Staedke SG, Smith DL, Greenhouse B, Dorsey G, , 2015. Malaria transmission, infection and disease at three sites with varied transmission intensity in Uganda: implications for malaria control. Am J Trop Med Hyg 92: 903912.[Crossref]
  31. Uganda Bureau of Statistics, 2011. Uganda Demographic and Health Survey. Kampala, Uganda: Uganda Bureau of Statistics.
  32. Uganda Bureau of Statistics, 2009. Uganda Malaria Indicator Survey. Kampala, Uganda: Uganda Bureau of Statistics.
  33. McKenzie DJ, , 2005. Measuring inequality with asset indicators. J Popul Econ 18: 229260.[Crossref]
  34. de Castro MC, Fisher MG, , 2012. Is malaria illness among young children a cause or a consequence of low socioeconomic status? Evidence from the united Republic of Tanzania. Malar J 11: 161.[Crossref]
  35. Arinaitwe E, Gasasira A, Verret W, Homsy J, Wanzira H, Kakuru A, Sandison TG, Young S, Tappero JW, Kamya MR, Dorsey G, , 2012. The association between malnutrition and the incidence of malaria among young HIV-infected and -uninfected Ugandan children: a prospective study. Malar J 11: 90.[Crossref]
  36. Wanzirah H, Tusting LS, Arinaitwe E, Katureebe A, Maxwell K, Rek J, Bottomley C, Staedke S, Kamya M, Dorsey G, Lindsay SW, , 2015. Mind the gap: house construction and the risk of malaria in Ugandan children. PLoS One 10: e0117396.[Crossref]
  37. Gwatkin DR, Rustsein S, Johnston K, Suliman E, Wagstaff A, , 2007. Socio-Economic Differences in Health, Nutrition and Population in Developing Countries: An Overview. Washington, DC: World Bank.
  38. Falkingham J, Namazie C, , 2002. Measuring Health and Poverty: A Review of Approaches to Identifying the Poor. London, United Kingdom: DFID Health Systems Resource Centre (HSRC).
  39. Pullan RL, Bukirwa H, Staedke SG, Snow RW, Brooker S, , 2010. Plasmodium infection and its risk factors in eastern Uganda. Malar J 9: 2.[Crossref]
  40. Gakidou E, Cowling K, Lozano RC, Murray CJ, , 2010. Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: a systematic analysis. Lancet 376: 959974.[Crossref]
  41. ILO, 2002. Women and Men in the Informal Economy: A Statistical Picture. Geneva, Switzerland: International Labor Organization.
http://instance.metastore.ingenta.com/content/journals/10.4269/ajtmh.15-0554
Loading
/content/journals/10.4269/ajtmh.15-0554
Loading

Data & Media loading...

  • Received : 30 Jul 2015
  • Accepted : 30 Nov 2015

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